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256 | **********************************************************************
*** Reproducing one-way ANOVA Tables
*** Valentim R. Alferes (University of Coimbra, Portugal)
*** valferes@fpce.uc.pt
** This syntax reproduces traditional one-way ANOVA Tables
** from summary statistics in published articles.
** You have four methods, depending on the available data.
**********************************************************************
** METHOD 1: Ns Means, and SDs.
* Enter, row by row, N, Mean and Standard Deviation for the
* groups or experimental treatments (in the example, you have
* three treatments).
DATA LIST LIST /n(F8.0) m(f8.2) sd(f8.2).
BEGIN DATA
6 10,50 2,30
7 11,34 3,60
8 15,17 4,10
END DATA.
COMPUTE iv=$CASENUM.
LOOP id=1 TO n.
XSAVE OUTFILE=XOUT1.
END LOOP.
EXECUTE.
GET FILE=XOUT1.
COMPUTE dv=m.
COMPUTE k=SQR((sd**2*(N-1))/2).
IF (id=1) dv=m+k.
IF (id=2) dv=m-k.
EXECUTE.
SUMMARIZE/TABLES=dv BY iv/FORMAT=NOLIST TOTAL
/TITLE='Case Summaries'/CELLS=COUNT MEAN STDDEV VAR.
ONEWAY dv BY iv.
**********************************************************************
** METHOD 2: Ns Means, and Variances.
* Enter, row by row, N, Mean and Variance for the
* groups or experimental treatments (in the example, you have
* three treatments).
DATA LIST LIST /n(F8.0) m(f8.2) var(f8.2).
BEGIN DATA
6 10,50 5,29
7 11,34 12,96
8 15,17 16,81
END DATA.
COMPUTE iv=$CASENUM.
LOOP id=1 TO n.
XSAVE OUTFILE=XOUT1.
END LOOP.
EXECUTE.
GET FILE=XOUT1.
COMPUTE dv=m.
COMPUTE k=SQR((var*(N-1))/2).
IF (id=1) dv=m+k.
IF (id=2) dv=m-k.
EXECUTE.
SUMMARIZE/TABLES=dv BY iv/FORMAT=NOLIST TOTAL
/TITLE='Case Summaries'/CELLS=COUNT MEAN STDDEV VAR.
ONEWAY dv BY iv.
**********************************************************************
** METHOD 3: Ns, Means, and MSError.
* Enter, row by row, N and Mean for the groups or experimental
* treatments (in the example, you have three treatments).
DATA LIST LIST /n(F8.0) m(f8.0).
BEGIN DATA
6 10,50
7 11,34
8 15,17
END DATA.
* Enter Mean Square Error.
COMPUTE mse = 12.32667.
COMPUTE iv=$CASENUM.
LOOP id=1 TO n.
XSAVE OUTFILE=XOUT1.
END LOOP.
EXECUTE.
GET FILE=XOUT1.
COMPUTE dv=m.
COMPUTE k=SQR((mse*(N-1))/2).
IF (id=1) dv=m+k.
IF (id=2) dv=m-k.
EXECUTE.
SUMMARIZE/TABLES=dv BY iv/FORMAT=NOLIST TOTAL
/TITLE='Case Summaries'/CELLS=COUNT MEAN.
ONEWAY dv BY iv.
**********************************************************************
** METHOD 4: Means, DFnum, DFden, and MSError.
* Enter, row by row, the Mean for the groups or experimental
* treatments (in the example, you have three treatments).
DATA LIST LIST /m(f8.2).
BEGIN DATA
10,50
11,34
15,17
END DATA.
* Enter degrees of freedom for numerator (between groups df).
COMPUTE dfnum=2.
* Enter degrees of freedom for denominator (within groups
* or MSError df).
COMPUTE dfden=18.
* Enter MSError.
COMPUTE mse=12.32667.
COMPUTE iv=$CASENUM.
COMPUTE n_tot=dfnum+dfden+1.
COMPUTE n_treat=dfnum+1.
COMPUTE nxi=RND(n_tot/n_treat).
EXECUTE.
CREATE cum=CSUM(nxi).
SORT CASES BY cum(D).
IF ($CASENUM=1) nxi=nxi-(cum-n_tot).
EXECUTE.
SORT CASES BY iv(A).
LOOP id=1 TO nxi.
XSAVE OUTFILE=XOUT1.
END LOOP.
EXECUTE.
GET FILE=XOUT1.
COMPUTE dv=m.
COMPUTE k=SQR((mse*(nxi-1))/2).
IF (id=1) dv=m+K.
IF (id=2) dv=m-K.
EXECUTE.
SUMMARIZE/TABLES=dv BY iv/FORMAT=NOLIST TOTAL
/TITLE='Case Summaries'/CELLS=COUNT MEAN.
ONEWAY dv BY iv.
**********************************************************************
** Note
** With Method 4 you don't know the Ns per treatment from the original
** source. If they are equal, you will get the exact ANOVA Table. Otherwise,
** as is the case in this example, you get only an approximation,
** because the syntax assumes that the Ns are equal in all treatments
** (if N_TOT/N_TREAT is an integer), or that they are equal in all
** treatments, except for the last one (if N_TOT/N_TREAT is not an integer).
**
** The syntax bellow exemplifies the case for equal Ns per treatment.
**********************************************************************
** The following syntax does the ANOVA on raw data from Kirk
**(1995, p. 167, Table 5.2-I) and compares it with Methods 1 and 4.
** Analysis of raw data from Kirk (1995, p. 167, Table 5.2-I).
DATA LIST FREE /IV(F8.0) DV(F8.0).
BEGIN DATA
1 4 1 6 1 3 1 3 1 1 1 3 1 2 1 2 2 4 2 5 2 4 2 3 2 2 2 3 2 4 2 3 3 5
3 6 3 5 3 4 3 3 3 4 3 3 3 4 4 3 4 5 4 6 4 5 4 6 4 7 4 8 4 10
END DATA.
ONEWAY dv BY iv/STATISTICS DESCRIPTIVES.
** METHOD 1: Ns Means, and SDs.
* Enter, row by row, N, Mean and Standard Deviation for the
* groups or experimental treatments (in the example, you have
* three treatments).
DATA LIST LIST /n(F8.0) m(f8.2) sd(f8.6).
BEGIN DATA
8 3,00 1,511858
8 3,50 0,925820
8 4,25 1,035098
8 6,25 2,121320
END DATA.
COMPUTE iv=$CASENUM.
LOOP id=1 TO n.
XSAVE OUTFILE=XOUT1.
END LOOP.
EXECUTE.
GET FILE=XOUT1.
COMPUTE dv=m.
COMPUTE k=SQR((sd**2*(N-1))/2).
IF (id=1) dv=m+k.
IF (id=2) dv=m-k.
EXECUTE.
SUMMARIZE/TABLES=dv BY iv/FORMAT=NOLIST TOTAL
/TITLE='Case Summaries'/CELLS=COUNT MEAN STDDEV VAR.
ONEWAY dv BY iv.
** METHOD 4: Means, DFnum, DFden, and MSError.
* Enter, row by row, the Mean for the groups or experimental
* treatments (in the example, you have three treatments).
DATA LIST LIST /m(f8.2).
BEGIN DATA
3,00
3,50
4,25
6,25
END DATA.
* Enter degrees of freedom for numerator (between groups df).
COMPUTE dfnum=3.
* Enter degrees of freedom for denominator (within groups
* or MSError df).
COMPUTE dfden=28.
* Enter MSError.
COMPUTE mse=2.178571.
COMPUTE iv=$CASENUM.
COMPUTE n_tot=dfnum+dfden+1.
COMPUTE n_treat=dfnum+1.
COMPUTE nxi=RND(n_tot/n_treat).
EXECUTE.
CREATE cum=CSUM(nxi).
SORT CASES BY cum(D).
IF ($CASENUM=1) nxi=nxi-(cum-n_tot).
EXECUTE.
SORT CASES BY iv(A).
LOOP id=1 TO nxi.
XSAVE OUTFILE=XOUT1.
END LOOP.
EXECUTE.
GET FILE=XOUT1.
COMPUTE dv=m.
COMPUTE k=SQR((mse*(nxi-1))/2).
IF (id=1) dv=m+K.
IF (id=2) dv=m-K.
EXECUTE.
SUMMARIZE/TABLES=dv BY iv/FORMAT=NOLIST TOTAL
/TITLE='Case Summaries'/CELLS=COUNT MEAN.
ONEWAY dv BY iv.
**********************************************************************
Kirk, R. E. (1995). Experimental design: Procedures for the behavioral
sciences (3rd ed.). Pacific Grove, CA: Brooks/Cole.
**********************************************************************.
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