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LazStats: improved report layout of BlkAnovaUnit.
git-svn-id: https://svn.code.sf.net/p/lazarus-ccr/svn@7491 8e941d3f-bd1b-0410-a28a-d453659cc2b4
This commit is contained in:
wp_xxyyzz
@ -574,7 +574,7 @@ object BlksAnovaFrm: TBlksAnovaFrm
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OnChange = VarChange
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ReadOnly = True
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TabOrder = 3
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Text = 'Edit1'
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Text = 'Factor1'
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end
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end
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object Panel3: TPanel
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@ -654,7 +654,7 @@ object BlksAnovaFrm: TBlksAnovaFrm
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OnChange = VarChange
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ReadOnly = True
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TabOrder = 3
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Text = 'Edit1'
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Text = 'Factor2'
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end
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end
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object Panel4: TPanel
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@ -734,7 +734,7 @@ object BlksAnovaFrm: TBlksAnovaFrm
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OnChange = VarChange
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ReadOnly = True
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TabOrder = 3
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Text = 'Edit1'
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Text = 'Factor3'
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end
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end
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object Bevel1: TBevel
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@ -86,42 +86,43 @@ type
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private
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{ private declarations }
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FAutoSized: Boolean;
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NoSelected, N : integer;
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ColNoSelected : IntDyneVec;
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outline, cellstring : string;
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SSDep, SSErr, SSF1, SSF2, SSF3, SSF1F2, SSF1F3, SSF2F3, SSF1F2F3 : double;
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MSDep, MSErr, MSF1, MSF2, MSF3, MSF1F2, MSF1F3, MSF2F3, MSF1F2F3 : double;
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DFTot, DFErr, DFF1, DFF2, DFF3, DFF1F2, DFF1F3, DFF2F3, DFF1F2F3 : double;
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Omega, OmegaF1, OmegaF2, OmegaF3, OmegaF1F2, F, MinSize, MaxSize : double;
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OmegaF1F3, OmegaF2F3, OmegaF1F2F3 : double;
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FF1, FF2, FF1F2, ProbF1, ProbF2, ProbF3, ProbF1F2, ProbF1F3 : double;
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FF3, FF2F3, FF1F3, FF1F2F3, ProbF2F3, ProbF1F2F3 : double;
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DepVarCol, F1Col, F2Col, F3Col, Nf1cells, Nf2cells, Nf3cells : integer;
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NoSelected, N: integer;
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ColNoSelected: IntDyneVec;
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outline, cellstring: string;
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SSDep, SSErr, SSF1, SSF2, SSF3, SSF1F2, SSF1F3, SSF2F3, SSF1F2F3: double;
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MSDep, MSErr, MSF1, MSF2, MSF3, MSF1F2, MSF1F3, MSF2F3, MSF1F2F3: double;
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DFTot, DFErr, DFF1, DFF2, DFF3, DFF1F2, DFF1F3, DFF2F3, DFF1F2F3: double;
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Omega, OmegaF1, OmegaF2, OmegaF3, OmegaF1F2, F: Double;
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MinSize: Double;
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OmegaF1F3, OmegaF2F3, OmegaF1F2F3: double;
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FF1, FF2, FF1F2, ProbF1, ProbF2, ProbF3, ProbF1F2, ProbF1F3: double;
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FF3, FF2F3, FF1F3, FF1F2F3, ProbF2F3, ProbF1F2F3: double;
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DepVarCol, F1Col, F2Col, F3Col, Nf1cells, Nf2cells, Nf3cells: integer;
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MeanDep, MeanF1, MeanF2, MeanF3: double;
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minf1, maxf1, minf2, maxf2, minf3, maxf3, nofactors, totcells : integer;
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cellcnts : IntDyneVec; // array of cell counts
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cellvars : DblDyneVec; // arrray of cell sums of squares then variances
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cellsums : DblDyneVec; // array of cell sums then means
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equal_grp : boolean; // check for equal groups for post-hoc tests
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counts : IntDyneMat; // matrix for 2-way containing cell sizes
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sums : DblDyneMat; // matrix for 2-way containing cell sums
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vars : DblDyneMat; // matrix for 2-way containing sums of squares
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RowSums : DblDyneVec; // 2 way row sums
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ColSums : DblDyneVec; // 2 way col sums
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RowCount : IntDyneVec; // 2 way row count
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ColCount : IntDyneVec; // 2 way col count
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SlcSums : DblDyneVec; // 3 way slice sums
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SlcCount : IntDyneVec; // 3 way slice counts
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NoGrpsA, NoGrpsB, NoGrpsC : integer;
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OrdMeansA, OrdMeansB, OrdMeansC : DblDyneVec; // reordered means for f1, f2, f3
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allAlpha, PostHocAlpha : double; // alphas for tests
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minf1, maxf1, minf2, maxf2, minf3, maxf3, nofactors, totcells: integer;
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cellcnts: IntDyneVec; // array of cell counts
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cellvars: DblDyneVec; // arrray of cell sums of squares then variances
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cellsums: DblDyneVec; // array of cell sums then means
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equal_grp: boolean; // check for equal groups for post-hoc tests
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counts: IntDyneMat; // matrix for 2-way containing cell sizes
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sums: DblDyneMat; // matrix for 2-way containing cell sums
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vars: DblDyneMat; // matrix for 2-way containing sums of squares
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RowSums: DblDyneVec; // 2 way row sums
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ColSums: DblDyneVec; // 2 way col sums
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RowCount: IntDyneVec; // 2 way row count
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ColCount: IntDyneVec; // 2 way col count
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SlcSums: DblDyneVec; // 3 way slice sums
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SlcCount: IntDyneVec; // 3 way slice counts
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NoGrpsA, NoGrpsB, NoGrpsC: integer;
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OrdMeansA, OrdMeansB, OrdMeansC: DblDyneVec; // reordered means for f1, f2, f3
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AllAlpha, PostHocAlpha: double; // alphas for tests
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// wsum : array[1..20,1..20,1..20] of double; // sums for 3 way
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// ncnt : array[1..20,1..20,1..20] of integer; // n in 3 way cells
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// wx2 : array[1..20,1..20,1..20] of double; // sums of squares for 3 way cells
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wsum, wx2 : DblDyneCube;
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ncnt : IntDyneCube;
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OKterms : array[1..14] of integer;
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CompError : boolean;
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wsum, wx2: DblDyneCube;
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ncnt: IntDyneCube;
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OKterms: array[1..14] of integer;
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CompError: boolean;
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procedure GetLevels;
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procedure Calc1Way;
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@ -234,8 +235,8 @@ begin
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begin
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DepVar.Text := VarList.Items[index];
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VarList.Items.Delete(index);
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end;
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UpdateBtnStates;
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end;
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end;
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procedure TBlksAnovaFrm.ComputeBtnClick(Sender: TObject);
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@ -356,7 +357,7 @@ begin
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if Bonferoni.Checked then
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Bonferroni(cellsums, cellcnts, cellvars, minf1, maxf1, posthocAlpha, lReport);
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if OrthoContrasts.Checked then
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Contrasts(MSErr, DFErr, cellsums, cellcnts, minf1, maxf1, 0.05, lReport);
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Contrasts(MSErr, DFErr, cellsums, cellcnts, minf1, maxf1, allAlpha, posthocAlpha, lReport);
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if BrownForsythe.Checked then
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BrownForsytheOneWay(lReport);
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if Welch.Checked then
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@ -479,8 +480,8 @@ begin
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begin
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VarList.Items.Add(Factor1.Text);
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Factor1.Text := '';
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end;
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UpdateBtnStates;
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end;
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end;
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procedure TBlksAnovaFrm.Fact2InClick(Sender: TObject);
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@ -492,8 +493,8 @@ begin
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begin
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Factor2.Text := VarList.Items[index];
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VarList.Items.Delete(index);
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end;
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UpdateBtnStates;
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end;
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end;
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procedure TBlksAnovaFrm.Fact2OutClick(Sender: TObject);
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@ -502,8 +503,8 @@ begin
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begin
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VarList.Items.Add(Factor2.Text);
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Factor2.Text := '';
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end;
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UpdateBtnStates;
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end;
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end;
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procedure TBlksAnovaFrm.Fact3InClick(Sender: TObject);
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@ -515,8 +516,8 @@ begin
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begin
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Factor3.Text := VarList.Items[index];
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VarList.Items.Delete(index);
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end;
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UpdateBtnStates;
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end;
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end;
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procedure TBlksAnovaFrm.Fact3OutClick(Sender: TObject);
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@ -525,8 +526,8 @@ begin
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begin
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VarList.Items.Add(Factor3.Text);
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Factor3.Text := '';
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end;
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UpdateBtnStates;
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end;
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end;
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procedure TBlksAnovaFrm.Fact1InClick(Sender: TObject);
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@ -538,8 +539,8 @@ begin
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begin
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Factor1.Text := VarList.Items[index];
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VarList.Items.Delete(index);
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end;
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UpdateBtnStates;
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end;
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end;
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procedure TBlksAnovaFrm.GetLevels;
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@ -647,23 +648,28 @@ var
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i, grpsize: integer;
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minvar, maxvar, sumvar, sumfreqlogvar, sumDFrecip: double;
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c, bartlett, cochran, hartley, chiprob: double;
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maxSize: Integer;
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begin
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AReport.Add(DIVIDER);
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AReport.Add('ONE WAY ANALYSIS OF VARIANCE RESULTS');
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AReport.Add(DIVIDER);
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AReport.Add('Dependent variable is: %s', [DepVar.Text]);
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AReport.Add('Independent variable is: %s', [Factor1.Text]);
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AReport.Add('');
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AReport.Add('Dependent variable is: %s, Independent variable is: %s', [DepVar.Text, Factor1.Text]);
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AReport.Add('');
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add(DIVIDER_SMALL);
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AReport.Add('SOURCE D.F. SS MS F PROB.>F OMEGA SQR.');
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add(DIVIDER_SMALL);
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AReport.Add('BETWEEN %4.0f%10.2f%10.2f%10.2f%10.2f%10.2f', [DFF1, SSF1, MSF1, F, ProbF1, Omega]);
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AReport.Add('WITHIN %4.0f%10.2f%10.2f', [DFErr, SSErr, MSErr]);
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AReport.Add('TOTAL %4.0f%10.2f', [DFTot, SSDep]);
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add(DIVIDER_SMALL);
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AReport.Add('');
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AReport.Add('MEANS AND VARIABILITY OF THE DEPENDENT VARIABLE');
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AReport.Add('FOR LEVELS OF THE INDEPENDENT VARIABLE');
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AReport.Add('');
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AReport.Add('MEANS AND VARIABILITY OF THE DEPENDENT VARIABLE FOR LEVELS OF THE INDEPENDENT VARIABLE');
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add('GROUP MEAN VARIANCE STD.DEV. N');
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Areport.Add('---------------------------------------------------------------------');
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AReport.Add('----- --------- ---------- ---------- ---------');
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// xxxx xxxxxxxxx xxxxxxxxxx xxxxxxxxxx xxxx
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equal_grp := true;
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minvar := 1e20;
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@ -673,7 +679,7 @@ begin
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sumfreqlogvar := 0.0;
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grpsize := round(cellcnts[0]);
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MinSize := grpsize; // initialized minimum group size
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MaxSize := grpsize; // initialize maximum group size
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maxSize := grpsize; // initialize maximum group size
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for i := 0 to NF1cells-1 do
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begin
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grpsize := round(cellcnts[i]);
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@ -682,8 +688,8 @@ begin
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MinSize := grpsize;
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equal_grp := false;
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end;
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if grpsize > MaxSize then
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MaxSize := grpsize;
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if grpsize > maxSize then
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maxSize := grpsize;
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if cellcnts[i] > 1 then
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begin
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@ -697,14 +703,14 @@ begin
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end;
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if cellcnts[i] > 0 then
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AReport.Add('%4d %10.2f%10.2f%10.2f%4d', [
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AReport.Add('%4d %9.2f %10.2f %10.2f %4d', [
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i+1, cellsums[i] / cellcnts[i], cellvars[i], sqrt(cellvars[i]), cellcnts[i]
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]);
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end;
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add('TOTAL%10.2f%10.2f%10.2f%4d', [MeanDep, MSDep, sqrt(MSDep), N]);
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add('---------------------------------------------------');
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AReport.Add('TOTAL%9.2f %10.2f %10.2f %4d', [MeanDep, MSDep, sqrt(MSDep), N]);
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AReport.Add('---------------------------------------------------');
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AReport.Add('');
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c := 1.0 + (1.0 / (3 * DFF1)) * (sumDFrecip - (1.0 / DFErr));
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@ -713,12 +719,14 @@ begin
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cochran := maxvar / sumvar;
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hartley := maxvar / minvar;
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AReport.Add(DIVIDER);
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AReport.Add('TESTS FOR HOMOGENEITY OF VARIANCE');
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add('Hartley Fmax test statistic = %.2f with deg.s freedom: %d and %.0f.', [hartley, NF1cells, MaxSize - 1]);
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AReport.Add('Cochran C statistic = %.2f with deg.s freedom: %d and %.0f.', [cochran, NF1cells, MaxSize - 1]);
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AReport.Add('Bartlett Chi-square = %0.2f with %.0f D.F. Prob. > Chi-Square = %.3f', [bartlett, DFF1, chiprob]);
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add('');
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AReport.Add('Hartley Fmax test statistic: %8.2f (%d and %d d.f.)', [hartley, NF1cells, maxSize-1]);
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AReport.Add('Cochran C statistic: %8.2f (%d and %d d.f.)', [cochran, Nf1cells, maxSize-1]);
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AReport.Add('Bartlett Chi-square: %8.2f (%.0f d.f)', [bartlett, DFF1]);
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AReport.Add(' probability > Chi-Square: %8.3f', [chiprob]);
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AReport.Add(DIVIDER);
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end;
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procedure TBlksAnovaFrm.OneWayPlot;
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@ -808,7 +816,7 @@ begin
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grpA := round(StrToFloat(Trim(OS3MainFrm.DataGrid.Cells[F1Col,i])));
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grpB := round(StrToFloat(Trim(OS3MainFrm.DataGrid.Cells[F2Col,i])));
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X := StrToFloat(Trim(OS3MainFrm.DataGrid.Cells[DepVarCol,i]));
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X := X*X;
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X2 := X*X;
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grpA := grpA - minf1 + 1;
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grpB := grpB - minf2 + 1;
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counts[grpA-1,grpB-1] := counts[grpA-1,grpB-1] + 1;
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@ -1057,12 +1065,13 @@ begin
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cochran := maxvar / sumvars;
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hartley := maxvar / minvar;
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AReport.Add(DIVIDER);
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AReport.Add('TESTS FOR HOMOGENEITY OF VARIANCE');
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add(DIVIDER_SMALL);
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AReport.Add('Hartley Fmax test statistic = %10.2f with deg.s freedom: %d and %d.', [hartley, NoGrpsA*NoGrpsB, groupsize-1]);
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AReport.Add('Cochran C statistic = %10.2f with deg.s freedom: %d and %d.', [cochran, NoGrpsA*NoGrpsB, groupsize - 1]);
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AReport.Add('Bartlett Chi-square statistic = %10.2f with %4d D.F. Prob. larger value = %6.3f', [bartlett, NoGrpsA*NoGrpsB - 1, chiprob]);
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add(DIVIDER);
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end;
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procedure TBlksAnovaFrm.TwoWayPlot;
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@ -1817,13 +1826,13 @@ begin
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chiprob := chisquaredprob(bartlett,round(NoGrpsA * NoGrpsB * NoGrpsC - 1));
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cochran := maxvar / sumvars;
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hartley := maxvar / minvar;
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AReport.Add(DIVIDER);
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AReport.Add('TESTS FOR HOMOGENEITY OF VARIANCE');
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add('Hartley Fmax test statistic = %.2f with deg.s freedom: %d and %d.', [hartley, NoGrpsA*NoGrpsB, groupsize-1]);
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AReport.Add(outline);
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AReport.Add('Cochran C statistic = %.2f with deg.s freedom: %d and %d.', [cochran, NoGrpsA*NoGrpsB, groupsize - 1]);
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AReport.Add('Bartlett Chi-square statistic = %.2f with %d D.F. Prob. larger = %.3f', [bartlett, NoGrpsA*NoGrpsB - 1, 1.0 - chiprob]);
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AReport.Add('---------------------------------------------------------------------');
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AReport.Add(DIVIDER_SMALL);
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AReport.Add('Hartley Fmax test statistic: %8.2f with deg.s freedom: %d and %d.', [hartley, NoGrpsA*NoGrpsB, groupsize-1]);
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AReport.Add('Cochran C statistic: %8.2f with deg.s freedom: %d and %d.', [cochran, NoGrpsA*NoGrpsB, groupsize - 1]);
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AReport.Add('Bartlett Chi-square statistic: %8.2f with %d D.F. Prob. larger: %.3f', [bartlett, NoGrpsA*NoGrpsB - 1, 1.0 - chiprob]);
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AReport.Add(DIVIDER);
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end;
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procedure TBlksAnovaFrm.ThreeWayPlot;
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@ -2087,7 +2096,7 @@ begin
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if Bonferoni.Checked then
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Bonferroni(RowSums, RowCount, variances, minf1, maxf1, posthocAlpha, AReport);
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if OrthoContrasts.Checked then
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Contrasts(MSErr, DFErr, RowSums, RowCount, minf1, maxf1, AllAlpha, AReport);
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Contrasts(MSErr, DFErr, RowSums, RowCount, minf1, maxf1, AllAlpha, posthocAlpha, AReport);
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end;
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// Do column comparisons
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@ -2118,7 +2127,7 @@ begin
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if Bonferoni.Checked then
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Bonferroni(ColSums, ColCount, variances, minf2, maxf2, posthocAlpha, AReport);
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if OrthoContrasts.Checked then
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Contrasts(MSErr, DFErr, ColSums, ColCount, minf2, maxf2, AllAlpha, AReport);
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Contrasts(MSErr, DFErr, ColSums, ColCount, minf2, maxf2, AllAlpha, postHocAlpha, AReport);
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end;
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// do simple effects for columns within each row
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@ -2153,7 +2162,7 @@ begin
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if Bonferoni.Checked then
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Bonferroni(cellsums, cellcnts, cellvars, minf2, maxf2, posthocAlpha, AReport);
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if OrthoContrasts.Checked then
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Contrasts(MSErr, DFErr, cellsums, cellcnts, minf2, maxf2, 0.05, AReport);
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Contrasts(MSErr, DFErr, cellsums, cellcnts, minf2, maxf2, allAlpha, PostHocAlpha, AReport);
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end;
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end;
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@ -2189,7 +2198,7 @@ begin
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if Bonferoni.Checked then
|
||||
Bonferroni(cellsums, cellcnts, cellvars, minf1, maxf1, posthocAlpha, AReport);
|
||||
if OrthoContrasts.Checked then
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf1, maxf1, 0.05, AReport);
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf1, maxf1, allAlpha, postHocAlpha, AReport);
|
||||
end;
|
||||
end;
|
||||
variances := nil;
|
||||
@ -2241,7 +2250,7 @@ begin
|
||||
if Bonferoni.Checked then
|
||||
Bonferroni(RowSums, RowCount, variances, minf1, maxf1, posthocAlpha, AReport);
|
||||
if OrthoContrasts.Checked then
|
||||
Contrasts(MSErr, DFErr, RowSums, RowCount, minf1, maxf1, AllAlpha, AReport);
|
||||
Contrasts(MSErr, DFErr, RowSums, RowCount, minf1, maxf1, allAlpha, postHocAlpha, AReport);
|
||||
end;
|
||||
|
||||
// Do column comparisons
|
||||
@ -2273,7 +2282,7 @@ begin
|
||||
if Bonferoni.Checked then
|
||||
Bonferroni(ColSums, ColCount, variances, minf2, maxf2, posthocAlpha, AReport);
|
||||
if OrthoContrasts.Checked then
|
||||
Contrasts(MSErr, DFErr, ColSums, ColCount, minf2, maxf2, AllAlpha, AReport);
|
||||
Contrasts(MSErr, DFErr, ColSums, ColCount, minf2, maxf2, allAlpha, posthocAlpha, AReport);
|
||||
end;
|
||||
|
||||
// Do slice comparisons
|
||||
@ -2305,7 +2314,7 @@ begin
|
||||
if Bonferoni.Checked then
|
||||
Bonferroni(SlcSums, SlcCount, variances, minf3, maxf3, posthocAlpha, AReport);
|
||||
if OrthoContrasts.Checked then
|
||||
Contrasts(MSErr, DFErr, SlcSums, SlcCount, minf3, maxf3, AllAlpha, AReport);
|
||||
Contrasts(MSErr, DFErr, SlcSums, SlcCount, minf3, maxf3, allAlpha, posthocAlpha, AReport);
|
||||
end;
|
||||
|
||||
// do simple effects for columns within each row
|
||||
@ -2343,7 +2352,7 @@ begin
|
||||
if Bonferoni.Checked then
|
||||
Bonferroni(cellsums, cellcnts, cellvars, minf2, maxf2, posthocAlpha, AReport);
|
||||
if OrthoContrasts.Checked then
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf2, maxf2, 0.05, AReport);
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf2, maxf2, allAlpha, posthocAlpha, AReport);
|
||||
end;
|
||||
end;
|
||||
|
||||
@ -2382,7 +2391,7 @@ begin
|
||||
if Bonferoni.Checked then
|
||||
Bonferroni(cellsums, cellcnts, cellvars, minf1, maxf1, posthocAlpha, AReport);
|
||||
if OrthoContrasts.Checked then
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf1, maxf1, 0.05, AReport);
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf1, maxf1, allAlpha, posthocAlpha, AReport);
|
||||
end;
|
||||
end;
|
||||
|
||||
@ -2420,7 +2429,7 @@ begin
|
||||
if Bonferoni.Checked then
|
||||
Bonferroni(cellsums, cellcnts, cellvars, minf2, maxf2, posthocAlpha, AReport);
|
||||
if OrthoContrasts.Checked then
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf2, maxf2, 0.05, AReport);
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf2, maxf2, allAlpha, posthocAlpha, AReport);
|
||||
end;
|
||||
end;
|
||||
|
||||
@ -2458,7 +2467,7 @@ begin
|
||||
if Bonferoni.Checked then
|
||||
Bonferroni(cellsums, cellcnts, cellvars, minf1, maxf1, posthocAlpha, AReport);
|
||||
if OrthoContrasts.Checked then
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf1, maxf1, 0.05, AReport);
|
||||
Contrasts(MSErr, DFErr, cellsums, cellcnts, minf1, maxf1, allAlpha, posthocAlpha, AReport);
|
||||
end;
|
||||
end;
|
||||
variances := nil
|
||||
@ -2539,18 +2548,21 @@ begin
|
||||
ProbF1 := probf(F,DFF1,DFErr);
|
||||
MeanDep := MeanDep / N;
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('BROWN-FORSYTHE ONE WAY ANALYSIS OF VARIANCE RESULTS');
|
||||
AReport.Add('');
|
||||
AReport.Add('Dependent variable is: %s, Independent variable is: %s', [DepVar.Text, Factor1.Text]);
|
||||
AReport.Add('');
|
||||
AReport.Add('Traditional One-Way ANOVA Results');
|
||||
AReport.Add('---------------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER_SMALL);
|
||||
AReport.Add('SOURCE D.F. SS MS F PROB.>F OMEGA SQR.');
|
||||
AReport.Add('---------------------------------------------------------------------');
|
||||
AReport.Add('-----------------------------------------------------------------------');
|
||||
AReport.Add('BETWEEN %4.0f%10.2f%10.2f%10.2f%10.2f%10.2f', [DFF1, SSF1, MSF1, F, ProbF1, Omega]);
|
||||
AReport.Add('WITHIN %4.0f%10.2f%10.2f', [DFErr, SSErr, MSErr]);
|
||||
AReport.Add('TOTAL %4.0f%10.2f', [DFTot, SSDep]);
|
||||
AReport.Add('---------------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
|
||||
sumc1 := 0.0;
|
||||
MSErr := 0.0;
|
||||
@ -2581,11 +2593,11 @@ begin
|
||||
ProbF1 := probf(NewF,DFF1, fdegfree);
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add('---------------------------------------------------------------------');
|
||||
AReport.Add('Brown-Forsythe F statistic = %.3f', [NewF]);
|
||||
AReport.Add('Brown-Forsythe denominator degrees of freedom = %.0f', [fdegfree]);
|
||||
AReport.Add('Brown-Forsythe F probability = %.3f', [probf1]);
|
||||
AReport.Add('---------------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('Brown-Forsythe F statistic: %8.3f', [NewF]);
|
||||
AReport.Add('Brown-Forsythe denominator degrees of freedom: %8.0f', [fdegfree]);
|
||||
AReport.Add('Brown-Forsythe F probability: %8.3f', [probf1]);
|
||||
AReport.Add(DIVIDER);
|
||||
|
||||
{
|
||||
if Outputfrm = nil then
|
||||
@ -2639,7 +2651,7 @@ begin
|
||||
if not GoodRecord(i,NoSelected,ColNoSelected) then continue;
|
||||
intvalue := round(StrToFloat(Trim(OS3MainFrm.DataGrid.Cells[F1Col,i])));
|
||||
X := StrToFloat(Trim(OS3MainFrm.DataGrid.Cells[DepVarCol,i]));
|
||||
X := X*X;
|
||||
X2 := X*X;
|
||||
intvalue := intvalue - minf1;
|
||||
cellcnts[intvalue] := cellcnts[intvalue] + 1;
|
||||
cellsums[intvalue] := cellsums[intvalue] + X;
|
||||
@ -2726,9 +2738,12 @@ begin
|
||||
// F := MSF1 / MSErr;
|
||||
// ProbF1 := probf(F,DFF1, DFErr);
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('WELCH ONE WAY ANALYSIS OF VARIANCE RESULTS');
|
||||
AReport.Add('');
|
||||
AReport.Add('Dependent variable is: %s, Independent variable is: %s', [DepVar.Text, Factor1.Text]);
|
||||
AReport.Add('Dependent variable is: %s', [DepVar.Text]);
|
||||
AReport.Add('Independent variable is: %s', [Factor1.Text]);
|
||||
AReport.Add('');
|
||||
{ OutputFrm.RichEdit.Lines.Add('---------------------------------------------------------------------');
|
||||
OutputFrm.RichEdit.Lines.Add('SOURCE D.F. SS MS F PROB.>F OMEGA SQR.');
|
||||
@ -2742,20 +2757,11 @@ begin
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
OutputFrm.RichEdit.Lines.Add('---------------------------------------------------------------------');
|
||||
OutputFrm.RichEdit.Lines.Add(''); }
|
||||
AReport.Add('Welch F statistic = %8.4f', [F]);
|
||||
AReport.Add('Welch denominator degrees of freedom = %3.0f', [v]);
|
||||
AReport.Add('Welch F statistic: %8.4f', [F]);
|
||||
AReport.Add('Welch denominator degrees of freedom: %8.0f', [v]);
|
||||
|
||||
probF1 := probf(F,DFF1,v);
|
||||
AReport.Add('Welch F probability = %5.3f', [probf1]);
|
||||
|
||||
{
|
||||
if OutputFrm = nil then
|
||||
OutputFrm := TOutputFrm.Create(Application)
|
||||
else
|
||||
OutputFrm.Clear;
|
||||
OutputFrm.AddLines(AReport);
|
||||
OutputFrm.ShowModal;
|
||||
}
|
||||
AReport.Add('Welch F probability: %8.3f', [probf1]);
|
||||
|
||||
WelchtTests(AReport);
|
||||
end;
|
||||
@ -2774,9 +2780,9 @@ begin
|
||||
NoCompares := Nf1cells;
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add('---------------------------------------------------------------------');
|
||||
AReport.Add('Welch t-tests among groups');
|
||||
AReport.Add('---------------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('WELCH T-TESTS AMONG GROUPS');
|
||||
AReport.Add(DIVIDER_SMALL);
|
||||
|
||||
for i := 1 to NoCompares - 1 do
|
||||
begin
|
||||
@ -2799,41 +2805,30 @@ begin
|
||||
denominator := term1 + term2;
|
||||
numerator := sqr((var1 / cellcnts[i-1]) + (var2 / cellcnts[j-1]));
|
||||
gnu := numerator / denominator;
|
||||
AReport.Add('degrees of freedom: %8.3f', [gnu]);
|
||||
AReport.Add('Ddegrees of freedom: %8.3f', [gnu]);
|
||||
|
||||
v := round(gnu);
|
||||
AReport.Add('Rounded degrees of freedom = %d', [v]);
|
||||
AReport.Add('Rounded degrees of freedom: %8d', [v]);
|
||||
|
||||
probability := probt(t,gnu);
|
||||
AReport.Add('Probability > t = %8.3f', [probability]);
|
||||
AReport.Add('Probability > t: %8.3f', [probability]);
|
||||
AReport.Add('');
|
||||
end;
|
||||
|
||||
AReport.Add('');
|
||||
end;
|
||||
|
||||
{
|
||||
if OutputFrm = nil then
|
||||
OutputFrm := TOutputFrm.Create(Application)
|
||||
else
|
||||
OutputFrm.Clear;
|
||||
OutputFrm.AddLines(AReport);
|
||||
OutputFrm.ShowModal;
|
||||
}
|
||||
end;
|
||||
|
||||
procedure TBlksAnovaFrm.UpdateBtnStates;
|
||||
begin
|
||||
DepIn.Enabled := VarList.ItemIndex > -1;
|
||||
DepIn.Enabled := (VarList.ItemIndex > -1) and (DepVar.Text = '');
|
||||
DepOut.Enabled := DepVar.Text <> '';
|
||||
|
||||
Fact1In.Enabled := VarList.ItemIndex > -1;
|
||||
Fact1In.Enabled := (VarList.ItemIndex > -1) and (Factor1.Text = '');
|
||||
Fact1Out.Enabled := Factor1.Text <> '';
|
||||
|
||||
Fact2In.Enabled := VarList.ItemIndex > -1;
|
||||
Fact2In.Enabled := (VarList.ItemIndex > -1) and (Factor2.Text = '');
|
||||
Fact2Out.Enabled := Factor2.Text <> '';
|
||||
|
||||
Fact3In.Enabled := VarList.ItemIndex > -1;
|
||||
Fact3In.Enabled := (VarList.ItemIndex > -1) and (Factor3.Text = '');
|
||||
Fact3Out.Enabled := Factor3.Text <> '';
|
||||
end;
|
||||
|
||||
|
||||
@ -22,7 +22,8 @@ procedure Tukey(
|
||||
min_grp : integer; { minimum group code }
|
||||
max_grp : integer; { maximum group code }
|
||||
Alpha : Double; { alpha value }
|
||||
AReport : TStrings);
|
||||
AReport : TStrings
|
||||
);
|
||||
|
||||
procedure ScheffeTest(
|
||||
error_ms : double; { mean squared residual }
|
||||
@ -32,7 +33,8 @@ procedure ScheffeTest(
|
||||
max_grp : integer; { code of last group }
|
||||
total_n : double; { total number of cases }
|
||||
Alpha : double; { alpha value for testing }
|
||||
AReport : TStrings);
|
||||
AReport : TStrings
|
||||
);
|
||||
|
||||
procedure Newman_Keuls(
|
||||
error_ms : double; { residual mean squared }
|
||||
@ -43,7 +45,8 @@ procedure Newman_Keuls(
|
||||
min_grp : integer; { lowest group code }
|
||||
max_grp : integer; { largest group code }
|
||||
Alpha : double; { alpha value for testing }
|
||||
AReport : TStrings);
|
||||
AReport : TStrings
|
||||
);
|
||||
|
||||
procedure Tukey_Kramer(
|
||||
error_ms : double; { residual mean squared }
|
||||
@ -54,7 +57,8 @@ procedure Tukey_Kramer(
|
||||
min_grp : integer; { code of lowest group }
|
||||
max_grp : integer; { code of highst group }
|
||||
Alpha : double; { Alpha value for testing }
|
||||
AReport : TStrings);
|
||||
AReport : TStrings
|
||||
);
|
||||
|
||||
procedure Contrasts(
|
||||
error_ms : double; { residual ms }
|
||||
@ -64,7 +68,9 @@ procedure Contrasts(
|
||||
min_grp : integer; { lowest code }
|
||||
max_grp : integer; { highest code }
|
||||
overall_probf : double; { prob of overall test }
|
||||
AReport : TStrings);
|
||||
Alpha : Double;
|
||||
AReport : TStrings
|
||||
);
|
||||
|
||||
procedure Bonferroni(
|
||||
group_total : DblDyneVec; { sum of scores in group }
|
||||
@ -73,7 +79,8 @@ procedure Bonferroni(
|
||||
min_grp : integer; { code of lowest group }
|
||||
max_grp : integer; { code of highst group }
|
||||
Alpha : Double; { Alpha value for testing }
|
||||
AReport : TStrings);
|
||||
AReport : TStrings
|
||||
);
|
||||
|
||||
procedure TukeyBTest(
|
||||
ErrorMS : double; { within groups error }
|
||||
@ -84,19 +91,22 @@ procedure TukeyBTest(
|
||||
max_grp : integer; { largest group code }
|
||||
groupsize : double; { size of groups (all equal) }
|
||||
Alpha : Double; { Alpha value for testing }
|
||||
AReport : TStrings);
|
||||
AReport : TStrings
|
||||
);
|
||||
|
||||
procedure HomogeneityTest(
|
||||
GroupCol : integer;
|
||||
VarColumn : integer;
|
||||
NoCases : integer);
|
||||
NoCases : integer
|
||||
);
|
||||
|
||||
|
||||
implementation
|
||||
|
||||
uses
|
||||
OutputUnit,
|
||||
BlkAnovaUnit;
|
||||
// OutputUnit,
|
||||
//BlkAnovaUnit,
|
||||
Utils;
|
||||
|
||||
procedure Tukey(error_ms : double; { mean squared for residual }
|
||||
error_df : double; { deg. freedom for residual }
|
||||
@ -108,7 +118,6 @@ procedure Tukey(error_ms : double; { mean squared for residual }
|
||||
Alpha : double; { alpha value }
|
||||
AReport : TStrings);
|
||||
var
|
||||
sig: boolean;
|
||||
divisor: double;
|
||||
df1: integer;
|
||||
contrast, mean1, mean2: double;
|
||||
@ -116,11 +125,14 @@ var
|
||||
i,j: integer;
|
||||
outline: string;
|
||||
begin
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(' Tukey HSD Test for Differences Between Means');
|
||||
AReport.Add(' alpha selected = %.2f', [Alpha]);
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('TUKEY HSD TEST FOR DIFFERENCES BETWEEN MEANS');
|
||||
AReport.Add('Alpha selected: %.2f', [Alpha]);
|
||||
AReport.Add('');
|
||||
AReport.Add('Groups Difference Statistic Probability Significant?');
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add('------- ---------- ---------- ------------ ------------');
|
||||
// xx - xx xxxxxxx q = xxxxxx xxxxxx YES
|
||||
|
||||
divisor := sqrt(error_ms / value );
|
||||
for i := min_grp to max_grp - 1 do
|
||||
@ -132,25 +144,20 @@ begin
|
||||
contrast := mean1 - mean2;
|
||||
outline := outline + format('%7.3f q = ',[contrast]);
|
||||
contrast := abs(contrast / divisor) ;
|
||||
outline := outline + format('%6.3f ',[contrast]);
|
||||
outline := outline + format('%6.3f',[contrast]);
|
||||
df1 := max_grp - min_grp + 1;
|
||||
q_stat := STUDENT(contrast,error_df,df1);
|
||||
outline := outline + format(' %6.4f',[q_stat]);
|
||||
|
||||
if alpha >= q_stat then
|
||||
sig := TRUE
|
||||
else
|
||||
sig := FALSE;
|
||||
|
||||
if sig = TRUE then
|
||||
outline := outline + ' YES '
|
||||
outline := outline + ' YES'
|
||||
else
|
||||
outline := outline + ' NO';
|
||||
|
||||
AReport.Add(outline);
|
||||
end;
|
||||
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
end;
|
||||
|
||||
procedure ScheffeTest(error_ms : double; { mean squared residual }
|
||||
@ -168,14 +175,15 @@ var
|
||||
i, j: integer;
|
||||
begin
|
||||
AReport.Add('');
|
||||
AReport.Add('----------------------------------------------------------------');
|
||||
AReport.Add(' Scheffe contrasts among pairs of means.');
|
||||
AReport.Add(' alpha selected = %.2f', [alpha]);
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('SCHEFFE CONTRASTS AMONG PAIRS OF MEANS');
|
||||
AReport.Add('Alpha selected: %.2f', [alpha]);
|
||||
AReport.Add('');
|
||||
AReport.Add('Group vs Group Difference Scheffe Critical Significant?');
|
||||
AReport.Add(' Statistic Value');
|
||||
AReport.Add('----------------------------------------------------------------');
|
||||
AReport.Add('-------------- ----------- --------- -------- ------------');
|
||||
|
||||
alpha := 1.0 - alpha ;
|
||||
alpha := 1.0 - alpha;
|
||||
for i:= min_grp to max_grp - 1 do
|
||||
for j := i + 1 to max_grp do
|
||||
begin
|
||||
@ -200,10 +208,9 @@ begin
|
||||
AReport.Add(outline);
|
||||
end;
|
||||
|
||||
AReport.Add('----------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
end;
|
||||
|
||||
{ ----------------------------------------------------------------------- }
|
||||
|
||||
procedure Newman_Keuls(error_ms : double; { residual mean squared }
|
||||
error_df : double; { deg. freedom for error }
|
||||
@ -224,11 +231,12 @@ var
|
||||
divisor : double;
|
||||
tempno : integer;
|
||||
df1 : integer;
|
||||
sig : boolean;
|
||||
outline : string;
|
||||
begin
|
||||
SetLength(groupno,max_grp-min_grp+1);
|
||||
for i := min_grp to max_grp do groupno[i-1] := i;
|
||||
SetLength(groupno, max_grp-min_grp+1);
|
||||
for i := min_grp to max_grp do
|
||||
groupno[i-1] := i;
|
||||
|
||||
for i := min_grp to max_grp - 1 do
|
||||
begin
|
||||
for j := i + 1 to max_grp do
|
||||
@ -249,17 +257,20 @@ begin
|
||||
end;
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add('----------------------------------------------------------------------');
|
||||
AReport.Add(' Neuman-Keuls Test for Contrasts on Ordered Means');
|
||||
AReport.Add(' alpha selected = %.2f', [alpha]);
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('NEUMAN_KEULS TEST FOR CONTRASTS ON ORDERED MEANS');
|
||||
AReport.Add('Alpha selected: %.2f', [alpha]);
|
||||
AReport.Add('');
|
||||
AReport.Add('Group Mean');
|
||||
AReport.Add('----- ---------');
|
||||
// xxx xxxxxxx
|
||||
for i := 1 to max_grp do
|
||||
AReport.Add('%3d %10.3f', [groupno[i-1], group_total[i-1] / group_count[i-1]]);
|
||||
AReport.Add('%3d %8.3f', [groupno[i-1], group_total[i-1] / group_count[i-1]]);
|
||||
AReport.Add('');
|
||||
|
||||
AReport.Add('Groups Difference Statistic d.f. Probability Significant?');
|
||||
AReport.Add('----------------------------------------------------------------------');
|
||||
AReport.Add('------- ---------- ---------- ------ ----------- ------------');
|
||||
// xx - xx xxxxxxx q = xxxxxx xx xxx xxxxxx YES
|
||||
divisor := sqrt(error_ms / value);
|
||||
for i := min_grp to max_grp - 1 do
|
||||
begin
|
||||
@ -275,15 +286,15 @@ begin
|
||||
outline := outline + Format('%6.3f %2d %3.0f ', [contrast, df1, error_df]);
|
||||
q_stat := STUDENT(contrast, error_df, df1);
|
||||
outline := outline + Format(' %6.4f', [q_stat]);
|
||||
if alpha > q_stat then sig := TRUE else sig := FALSE;
|
||||
if sig = TRUE then
|
||||
if alpha > q_stat then
|
||||
outline := outline + ' YES'
|
||||
else
|
||||
outline := outline + ' NO';
|
||||
AReport.Add(outline);
|
||||
end;
|
||||
end;
|
||||
AReport.Add('----------------------------------------------------------------------');
|
||||
|
||||
AReport.Add(DIVIDER);
|
||||
groupno := nil;
|
||||
end;
|
||||
|
||||
@ -299,7 +310,6 @@ procedure Tukey_Kramer(error_ms : double; { residual mean squared }
|
||||
Alpha : Double; { Alpha value for testing }
|
||||
AReport : TStrings);
|
||||
var
|
||||
sig : boolean;
|
||||
divisor : double;
|
||||
df1 : integer;
|
||||
contrast, mean1, mean2 : double;
|
||||
@ -309,11 +319,13 @@ var
|
||||
|
||||
begin
|
||||
AReport.Add('');
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(' Tukey-Kramer Test for Differences Between Means');
|
||||
AReport.Add(' alpha selected = %.2f', [Alpha]);
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('TUKEY-KRAMER TEST FOR DIFFERENCES BETWEEN MEANS');
|
||||
AReport.Add('Alpha selected: %.2f', [Alpha]);
|
||||
AReport.Add('');
|
||||
AReport.Add('Groups Difference Statistic Probability Significant?');
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add('------ ---------- ------------- ----------- -------------');
|
||||
// xx -xx xxxxxxx q = xxxxxx xxxxxx yes
|
||||
|
||||
for i := min_grp to max_grp - 1 do
|
||||
for j := i + 1 to max_grp do
|
||||
@ -329,17 +341,15 @@ begin
|
||||
df1 := max_grp - min_grp + 1;
|
||||
q_stat := STUDENT(contrast,error_df,df1);
|
||||
outline := outline + format(' %6.4f',[q_stat]);
|
||||
if alpha >= q_stat then sig := TRUE else sig := FALSE;
|
||||
if sig = TRUE then
|
||||
if alpha >= q_stat then
|
||||
outline := outline + ' YES '
|
||||
else
|
||||
outline := outline + ' NO';
|
||||
AReport.Add(outline);
|
||||
end;
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
end;
|
||||
|
||||
{ ------------------------------------------------------------------------ }
|
||||
|
||||
procedure Contrasts(error_ms : double; { residual ms }
|
||||
error_df : double; { residual df }
|
||||
@ -348,20 +358,21 @@ procedure Contrasts(error_ms : double; { residual ms }
|
||||
min_grp : integer; { lowest code }
|
||||
max_grp : integer; { highest code }
|
||||
overall_probf : double; { prob of overall test }
|
||||
Alpha : Double; { prob of posthoc test }
|
||||
AReport : TStrings);
|
||||
var
|
||||
nocontrasts, i, j, k : integer;
|
||||
df1, df2, probstat, statistic, alpha : double;
|
||||
coefficients : array[1..20,1..20] of double;
|
||||
nonorthog : boolean;
|
||||
weight, sumcross : double;
|
||||
response : string[5];
|
||||
outline : string;
|
||||
prompt : string;
|
||||
nocontrasts, i, j, k: integer;
|
||||
df1, df2, probstat, statistic: double;
|
||||
coefficients: array[1..20,1..20] of double;
|
||||
nonorthog: boolean;
|
||||
weight, sumcross: double;
|
||||
response: string[5];
|
||||
outline: string;
|
||||
prompt: string;
|
||||
|
||||
begin
|
||||
outline := format('Enter the number of contrasts (less than %2d or 0:',[max_grp-min_grp+1]);
|
||||
response := InputBox('ORTHOGONAL CONTRASTS',outline,'0');
|
||||
outline := format('Enter the number of contrasts (less than %d or 0:', [max_grp-min_grp+1]);
|
||||
response := InputBox('ORTHOGONAL CONTRASTS', outline, '0');
|
||||
nocontrasts := StrToInt(response);
|
||||
|
||||
if nocontrasts > 0 then
|
||||
@ -371,43 +382,41 @@ begin
|
||||
outline := format('Contrast number %2d',[i]);
|
||||
for j := 1 to (max_grp - min_grp+1) do
|
||||
begin
|
||||
prompt := format('Group %2d coefficient = ',[j]);
|
||||
response := InputBox(outline,prompt,'1');
|
||||
prompt := format('Group %2d coefficient: ',[j]);
|
||||
response := InputBox(outline, prompt, '1');
|
||||
coefficients[i,j] := StrToFloat(response);
|
||||
end;
|
||||
end;
|
||||
|
||||
{ Check for orthogonality }
|
||||
nonorthog := FALSE;
|
||||
nonorthog := false;
|
||||
for i := 1 to nocontrasts - 1 do
|
||||
begin
|
||||
for j := i + 1 to nocontrasts do
|
||||
begin
|
||||
sumcross := 0;
|
||||
for k := 1 to (max_grp - min_grp + 1) do
|
||||
begin
|
||||
sumcross := sumcross + coefficients[i,k]*coefficients[j,k];
|
||||
end;
|
||||
if sumcross <> 0 then nonorthog := TRUE;
|
||||
if sumcross <> 0 then
|
||||
begin
|
||||
MessageDlg(Format('Contrasts %2d and %2d not orthogonal.',[i,j]), mtError, [mbOK], 0);;
|
||||
nonorthog := true;
|
||||
MessageDlg(Format('Contrasts %2d and %2d not orthogonal.', [i,j]), mtError, [mbOK], 0);;
|
||||
end;
|
||||
end;
|
||||
end;
|
||||
|
||||
if not nonorthog then
|
||||
begin
|
||||
alpha := StrToFloat(BlksAnovaFrm.PostAlpha.Text);
|
||||
if overall_probf > alpha then
|
||||
if overall_probf > Alpha then
|
||||
begin
|
||||
AReport.Add('No contrasts significant.');
|
||||
exit;
|
||||
end;
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(' ORTHOGONAL CONTRASTS');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('ORTHOGONAL CONTRASTS');
|
||||
AReport.Add('');
|
||||
AReport.Add('Contrast Statistic Probability Critical Value Significant?');
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
|
||||
@ -425,7 +434,7 @@ begin
|
||||
outline := Format('%3d %9.4f ', [i, statistic]);
|
||||
df1 := 1;
|
||||
df2 := error_df;
|
||||
probstat := probf(statistic,round(df1),round(df2)) / 2;
|
||||
probstat := probf(statistic, round(df1), round(df2)) / 2;
|
||||
outline := outline + Format('%8.3f %5.2f ', [probstat, alpha]);
|
||||
if probstat < alpha then
|
||||
outline := outline + 'YES'
|
||||
@ -443,7 +452,7 @@ begin
|
||||
AReport.Add(outline);
|
||||
end;
|
||||
end; { if orthogonal }
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
end; { if nocontrasts > 0 }
|
||||
end; { of procedure CONTRASTS }
|
||||
|
||||
@ -463,20 +472,22 @@ var
|
||||
testalpha : double;
|
||||
NoGrps : integer;
|
||||
tprob : double;
|
||||
sig : string[6];
|
||||
sig : string;
|
||||
SS1, SS2 : double;
|
||||
begin
|
||||
AReport.Add('');
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(' Bonferroni Test for Differences Between Means');
|
||||
AReport.Add(' Overall alpha selected = %.2f', [alpha]);
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('BONFERRONI TEST FOR DIFFERENCES BETWEEN MEANS');
|
||||
AReport.Add('Overall alpha selected: %.2f', [alpha]);
|
||||
AReport.Add('');
|
||||
|
||||
NoGrps := max_grp - min_grp + 1;
|
||||
testalpha := alpha / ( (NoGrps * (NoGrps-1)) / 2.0 );
|
||||
AReport.Add('Comparisons made at alpha / no. comparisons = %5.3f', [testalpha]);
|
||||
AReport.Add('Comparisons made at alpha / no. comparisons: %5.3f', [testalpha]);
|
||||
AReport.Add('');
|
||||
AReport.Add('Groups Difference Statistic Prob > Value Significant?');
|
||||
AReport.Add('------- ------------ --------- ------------ ------------');
|
||||
// xx - xx xxxxxxxxxx xxxxxxxxxx xxxxxxxxxx YES
|
||||
for i := 1 to NoGrps - 1 do
|
||||
begin
|
||||
for j := i+1 to NoGrps do
|
||||
@ -491,11 +502,13 @@ begin
|
||||
df2 := round(group_count[i-1] + group_count[j-1] - 2.0);
|
||||
tprob := probt(contrast,df2);
|
||||
if testalpha >= tprob then sig := 'YES' else sig := 'NO';
|
||||
AReport.Add('%3d - %3d %10.3f %10.3f %10.3f %s', [
|
||||
AReport.Add('%2d - %2d %10.3f %10.3f %10.3f %s', [
|
||||
min_grp+i-1, min_grp+j-1, mean1-mean2, contrast, tprob, sig
|
||||
]);
|
||||
end;
|
||||
end;
|
||||
|
||||
AReport.Add(DIVIDER);
|
||||
end;
|
||||
//-------------------------------------------------------------------
|
||||
|
||||
@ -520,7 +533,7 @@ var
|
||||
NoGrps: integer;
|
||||
contrast: double;
|
||||
mean1, mean2: double;
|
||||
sig: string[6];
|
||||
sig: string;
|
||||
groups: double;
|
||||
divisor: double;
|
||||
|
||||
@ -528,12 +541,13 @@ begin
|
||||
SetLength(groupno,max_grp-min_grp+1);
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(' Tukey B Test for Contrasts on Ordered Means');
|
||||
AReport.Add(' alpha selected = %.2f',[alpha]);
|
||||
AReport.Add('---------------------------------------------------------------');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('TUKEY B TEST FOR CONTRASTS ON ORDERED MEANS');
|
||||
AReport.Add('Alpha selected: %.2f',[alpha]);
|
||||
AReport.Add('');
|
||||
AReport.Add('Groups Difference Statistic d.f. Prob.>value Significant?');
|
||||
AReport.Add('------- ----------- --------- -------- ----------- ------------');
|
||||
// xx - xx xxxxxxxxxx xxxxxxxxxx xxx,xxx xxxxxxxx YES
|
||||
|
||||
divisor := sqrt(ErrorMS / groupsize);
|
||||
NoGrps := max_grp - min_grp + 1;
|
||||
@ -570,36 +584,34 @@ begin
|
||||
tstat := STUDENT(contrast,ErrorDF,groups);
|
||||
qstat := (qstat + tstat) / 2.0;
|
||||
if alpha >= qstat then sig := 'YES' else sig := 'NO';
|
||||
AReport.Add('%3d - %3d %10.3f %10.3f %4.0f,%4.0f %5.3f %s', [
|
||||
AReport.Add('%2d - %2d %10.3f %10.3f %3.0f,%3.0f %8.3f %s', [
|
||||
groupno[i-1], groupno[j-1], mean1-mean2, contrast, df1, ErrorDF, qstat, sig
|
||||
]);
|
||||
end;
|
||||
end;
|
||||
|
||||
AReport.Add(DIVIDER);
|
||||
groupno := nil;
|
||||
end;
|
||||
|
||||
procedure HomogeneityTest(GroupCol : integer;
|
||||
VarColumn : integer;
|
||||
NoCases : integer);
|
||||
Var
|
||||
i, j, k, N, intvalue, Nf1cells: integer;
|
||||
min, max : integer;
|
||||
zscores : DblDyneMat;
|
||||
medians : DblDyneVec;
|
||||
cellcnts : IntDyneVec;
|
||||
cellvars : DblDyneVec;
|
||||
cellsums : DblDyneVec;
|
||||
X, X2, temp : double;
|
||||
procedure HomogeneityTest(GroupCol: integer; VarColumn: integer; NoCases: integer);
|
||||
var
|
||||
i, j, k, intvalue, Nf1cells: integer;
|
||||
min, max: integer;
|
||||
zscores: DblDyneMat;
|
||||
medians: DblDyneVec;
|
||||
cellcnts: IntDyneVec;
|
||||
X: Double;
|
||||
begin
|
||||
if GroupCol >= OS3MainFrm.DataGrid.ColCount then
|
||||
begin
|
||||
MessageDlg('Invalid index of group column', mtError, [mbOK], 0);
|
||||
ErrorMsg('Invalid index of group column');
|
||||
exit;
|
||||
end;
|
||||
|
||||
if VarColumn >= OS3MainFrm.DataGrid.ColCount then
|
||||
begin
|
||||
Messagedlg('Invalid index of variable column', mtError, [mbOK], 0);
|
||||
ErrorMsg('Invalid index of variable column');
|
||||
exit;
|
||||
end;
|
||||
|
||||
@ -607,9 +619,8 @@ begin
|
||||
// between between the observed score and the median of a group.
|
||||
|
||||
// get min and max group codes
|
||||
min := 100000;
|
||||
max := 0;
|
||||
N := 0;
|
||||
min := MaxInt;
|
||||
max := -MaxInt;
|
||||
|
||||
for i := 1 to NoCases do
|
||||
begin
|
||||
@ -619,18 +630,16 @@ begin
|
||||
end;
|
||||
Nf1cells := max - min + 1;
|
||||
|
||||
setlength(zscores,Nf1cells,NoCases);
|
||||
setlength(medians,Nf1cells);
|
||||
setlength(cellcnts,Nf1cells);
|
||||
setlength(cellvars,Nf1cells);
|
||||
setlength(cellsums,Nf1cells);
|
||||
SetLength(zscores, Nf1cells, NoCases);
|
||||
SetLength(medians, Nf1cells);
|
||||
SetLength(cellcnts, Nf1cells);
|
||||
|
||||
// Get cell counts
|
||||
for i := 1 to NoCases do
|
||||
for i := 0 to NoCases-1 do
|
||||
begin
|
||||
intvalue := round(StrToFloat(Trim(OS3MainFrm.DataGrid.Cells[GroupCol,i])));
|
||||
intvalue := intvalue - min + 1;
|
||||
cellcnts[intvalue-1] := cellcnts[intvalue-1] + 1;
|
||||
intvalue := intvalue - min;
|
||||
cellcnts[intvalue] := cellcnts[intvalue] + 1;
|
||||
end;
|
||||
|
||||
// get working totals
|
||||
@ -644,56 +653,38 @@ begin
|
||||
intvalue := intvalue - min;
|
||||
if intvalue <> j then continue;
|
||||
X := StrToFloat(Trim(OS3MainFrm.DataGrid.Cells[VarColumn,i]));
|
||||
zscores[intvalue,k] := X;
|
||||
zscores[intvalue, k] := X;
|
||||
k := k + 1;
|
||||
end;
|
||||
end;
|
||||
|
||||
//sort on z scores and obtain the median for each group
|
||||
for i := 0 to Nf1cells-1 do // sort scores in each group
|
||||
begin
|
||||
for j := 0 to cellcnts[i]-2 do
|
||||
begin
|
||||
for k := j+1 to cellcnts[i]-1 do
|
||||
begin
|
||||
X := zscores[i,j];
|
||||
X2 := zscores[i,k];
|
||||
if X2 < X then // swap
|
||||
begin
|
||||
temp := X;
|
||||
X := X2;
|
||||
X2 := temp;
|
||||
end;
|
||||
end;
|
||||
end;
|
||||
end;
|
||||
if zscores[i, j] < zscores[i, k] then // swap
|
||||
Exchange(zscores[i, j], zscores[i, k]);
|
||||
|
||||
for i := 0 to Nf1cells-1 do
|
||||
begin
|
||||
medians[i] := zscores[i,cellcnts[i] div 2];
|
||||
end;
|
||||
medians[i] := zscores[i, cellcnts[i] div 2];
|
||||
|
||||
// Get deviations from the medians
|
||||
for i := 0 to Nf1cells-1 do
|
||||
begin
|
||||
for j := 0 to cellcnts[i]-1 do
|
||||
zscores[i,j] := zscores[i,j] - medians[i];
|
||||
end;
|
||||
|
||||
// place group membership and z deviation scores in columns and
|
||||
// do a regular one-way ANOVA
|
||||
k := 0;
|
||||
for i := 0 to Nf1cells-1 do
|
||||
begin
|
||||
for j := 0 to cellcnts[i]-1 do
|
||||
begin
|
||||
k := k +1;
|
||||
OS3MainFrm.DataGrid.Cells[GroupCol,k] := IntToStr(i+1);
|
||||
OS3MainFrm.DataGrid.Cells[VarColumn,k] := FloatToStr(abs(zscores[i,j]));
|
||||
end;
|
||||
end;
|
||||
|
||||
MessageDlg('Data have been placed in the grid. Do a one-way ANOVA', mtInformation, [mbOK], 0);
|
||||
MessageDlg('Data have been placed in the grid. Do a one-way ANOVA.', mtInformation, [mbOK], 0);
|
||||
end;
|
||||
|
||||
end.
|
||||
|
||||
Reference in New Issue
Block a user