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Intro

Effect Size Determination ProgramLast Updated 07/25/2001byDavid B. Wilson, Ph.D.University of Maryland, College Park

Introduction

The Effect Size Determination Program is for use with the book Practical Meta-Analysis written by Mark W. Lipsey and David B. Wilson and published by Sage. The creation of this program was supported by HSRI.

This program computes standardized mean difference effect sizes (d) and the correlation coefficients (r) from summary statistics, such as means and standard deviations, t-tests, frequencies, etc. It is useful during the coding phase of a meta-analysis for converting reported results into an effect size index.

To use, "click" on the "Main Menu" button with the mouse. From the Main Menu, select the desired transformation, again by "clicking" on the approrpiate button. Enter the requested data in all cells that are shaded in yellow. The effect size is computed automatically when all necessary data cells are filled in.

Menu

Main Menu

Means & SDs

Means and Standard Deviation, Post-Treatment Scores

Treatment Group Comparison GroupMean = Mean =

SD = SD =n = n =

d = r =

Means & SDs

Means & t-test

Means and t-test, Post-Treatment Scores


n = n =

t-value = d = r =

Means & t-test

Mean Gain Scores

Mean Gain Scores and Gain Score Standard Deviation


SD = SD =n = n =

Pre & Post-Test Scores Correlation =

d = r =

Mean Gain Scores

t-test (Independent)

Independent t-test, No Means Reported

t-value = d = Treatment n = r =

Comparsion n =

t-test (Independent)

t-test (p-value only)

Independent t-test, p-value only

p-value = d = df = r =

Note: This will always return a positive value

t-test (p-value only)

t-test (Dependent)

Dependent t-test, No Means Reported

t-value = d = n (pairs) = r =

r for paired values =

t-test (Dependent)

Proportions1

Proportion or Frequency (Dichotomous)

Logit Method Probit MethodFrequency with Positive Outcome d = d =

Treatment Group Successes = r = r = Treatment Group n =

Control Group Successes = Control Group n =

Logit Method Probit MethodProportion with Positive Outcome d = d =

Treatment Group = r = r = Control Group =

Logit = logged odds-ratio

Proportions1

Proportions2

Proportions (Ordinal Polychotomous)

Treatment Group Comparison Group Tx Group n =Values Percent Values Percent

0 0 Comp Grp n =1 12 2 Tx Mean =3 3 Tx SD =4 45 5 Comp Mean =6 6 Comp SD =7 78 8 d = 9 9 r =

Proportions2

Frequencies

Frequencies (Ordinal Polychotomous)

Treatment Group Comparison Group Tx Mean =Values Frequency Values Frequency Tx SD =

0 01 1 Comp Mean =2 2 Comp SD =3 34 4 d = 5 5 r = 6 67 78 89 9

Frequencies

F-test (k=2)

Oneway ANOVA with Two Groups (k=2)

F-value = d = Treatment n = r =

Comparison n =Note: This will always return a positive value

F-test (k=2)

F-test (k>2)

Oneway ANOVA with Three or More Groups (k>2)

Indicate MSw =Means n Group Type*

Method 1:d = r =

F-value =

Method 2:d = r =

Group Type: 1 = treatment group, -1 = comparison group, 0 = other

F-test (k>2)

Oneway ANCOVA

Oneway Analysis of Covariance


MS error = d = df error = r =

r* =

r* = correlation between the covariate and the dependent measure

Oneway ANCOVA

Chi-Square

Chi-Square (df=1)

Chi-Square = d = r =


Total N =

Chi-Square

Chi-Square (p-value only)

Chi-Square, p-value only (df=1)

p-value = d = r =


Total N =

Chi-Square (p-value only)

Correlation

Correlation and Mean Difference Effect Size Conversion

r = 0.23 d = 0.4727

d = 0.47 r = 0.2288

Correlation

Weighted Mean

Weighted Mean

Means n Weighted Mean =

Weighted Mean

Pooled SD

Pooled SD

SDs n Pooled SD =

Pooled SD

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