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| For B between subject factors with levels $$b_{i}$$, i=1, ..., B and W with subject factors with levels $$w_{i}$$, j=1, ..., W | For B between subject factors with levels $$b_{i}$$, i=1, ..., B and W with subject factors with levels $$w_{j}$$, j=1, ..., W |
- alpha is likelihood of making a type I error (usually = 0.05)
- etasq is partial eta-squared/100 so, for example, 5.9% = 0.059
Partial Eta-squared = SS(effect) divided by the sum of the SS(effect) and SS(its error)
or, in other words, the proportion of variance in outcome predicted by the effect after adjusting for other terms in the anova
For B between subject factors with levels $$b_{i}$$, i=1, ..., B and W with subject factors with levels $$w_{j}$$, j=1, ..., W
- num(erator) = $$ \prod_{\mbox{factors}} $$ (number of levels of factor -1) in term of interest
d1 = $$\sum_{i}^{B} (b_{i} - 1) $$ if B > 0 in anova
- = 0 otherwise
d2 = $$ \prod_{j} (w_{j} - 1) $$ if W > 0 in term of interest
- = 1 otherwise
- power is the power of the test
[ COPY AND PASTE THE BOXED BELOW SYNTAX BELOW INTO A SPSS SYNTAX WINDOW AND RUN; ADJUST INPUT DATA AS REQUIRED]
DATA LIST free
/alpha etasq num d1 d2 power.
BEGIN DATA.
.05 0.02 2 3 2 0.23
.05 0.12 2 3 2 0.93
END DATA.
matrix.
get m /variables=alpha etasq num d1 d2 power /missing=omit.
compute alpha=make(1,1,0).
compute etasq=make(1,1,0).
compute num=make(1,1,0).
compute d1=make(1,1,0).
compute d2=make(1,1,0).
compute power=make(1,1,0).
compute alpha=m(:,1).
compute etasq=m(:,2).
compute num=m(:,3).
compute d1=m(:,4).
compute d2=m(:,5).
compute power=m(:,6).
end matrix.
define apow (!pos !tokens(1)
/ !pos !tokens(1)
/ !pos !tokens(1)
/ !pos !tokens(1)
/ !pos !tokens(1)
/ !pos !tokens(1)).
COMPUTE #POW = !6.
compute #conf = (1-!1).
compute #lc3 = 1.
compute #ind=0.
compute ntot = 700.000.
comment COMPUTE #LC1 = 2.000.
compute denom=(ntot-1-!4)*!5.
COMPUTE #CUMF2 = 1 - NCDF.F(IDF.F(#conf,!3,denom),!3,denom,denom*!2/(1-!2)).
COMPUTE #DIFF=1.
SET MXLOOPS=10000.
LOOP IF (#DIFF GT .00005) .
+ DO IF (#CUMF2 GT #pow) .
+ COMPUTE #LC3 = ntot.
+ COMPUTE ntot = (Ntot - rnd(1)).
+ COMPUTE denom=(ntot-1-!4)*!5.
+ COMPUTE #CUMF2 = 1 - NCDF.F(IDF.F(#conf,!3,denom),!3,denom,denom*!2/(1-!2)).
+ ELSE .
+ COMPUTE #LC1 = ntot.
+ COMPUTE ntot = (ntot + #LC3)/2.
+ COMPUTE denom=(ntot-1-!4)*!5.
+ COMPUTE #CUMF2 = 1 - NCDF.F(IDF.F(#conf,!3,denom),!3,denom,denom*!2/(1-!2)).
+ END IF.
+ COMPUTE #DIFF = ABS(#CUMF2 - #pow) .
END LOOP .
compute pow2 = 1 - NCDF.F(IDF.F(#conf,!3,denom),!3,denom,denom*!2/(1-!2)).
if (ntot-trunc(ntot) gt 0.5) #ind=1.
if (#ind eq 0) ntot=trunc(ntot)+1.
if (#ind eq 1) ntot=rnd(ntot).
EXECUTE .
compute alpha=!1.
compute etasq=!2.
compute num=!3.
compute d1=!4.
compute d2=!5.
compute power=!6.
compute denom=(ntot-1-d1)*d2.
formats ntot (f7.0) alpha (f5.2) num (f5.2) denom (f5.2) etasq (f5.2) power (f5.2).
variable labels ntot 'Total Sample Size Required' /alpha 'Alpha' /num 'Numerator' /denom 'Denominator' /etasq 'Partial Eta-Sq' /power 'Power'.
report format=list automatic align(center)
/variables=ntot alpha num denom etasq power
/title "Anova term sample size for given power (any anova)" .
!enddefine.
matrix.
get m /variables=alpha etasq num d1 d2 power /missing=omit.
compute alpha=make(1,1,0).
compute etasq=make(1,1,0).
compute num=make(1,1,0).
compute d1=make(1,1,0).
compute d2=make(1,1,0).
compute power=make(1,1,0).
compute alpha=m(:,1).
compute etasq=m(:,2).
compute num=m(:,3).
compute d1=m(:,4).
compute d2=m(:,5).
compute power=m(:,6).
end matrix.
apow alpha etasq num d1 d2 power.