CODEWITHSUNDEEP
rstatisticsdata-analysis
user8460166
user8460166

Reputation: 173

Is there any way to calculate effect size between a pre-test and a post-test when scores on pre-test is 0 (or almost 0)

I would like to calculate an effect size between scores from pre-test and post-test of my studies.

However, due to the nature of my research, pre-test scores are usually 0 or almost 0 (before the treatment, participants usually do not have any knowledge in question).

I cannot just use Cohen's d to calculate effect sizes since the pre-test scores do not follow a normal distribution.

Is there any way I can calculate effect sizes in this case?

Any suggestions would be greatly appreciated.

Upvotes: 0

Views: 1128

Answers (1)

KenHBS
KenHBS

Reputation: 7164

You are looking for Cohen's d to see if the difference between the two time points (pre- and post-treatment) is large or small. The Cohen's d can be calculated as follows:

(mean_post - mean_pre) / {(variance_post + variance_pre)/2}^0.5

Where variance_post and variance_pre are the sample variances. Nowhere does it require here that the pre- and post-treatment score are normally distributed.

There are multiple packages available in R that provide a function for Cohen's d: effsize, pwr and lsr. In lsr your R-code would look like this:

library(lsr)
cohensD(pre_test_vector, post_test_vector)

Sidenote: The average scores tend to a normal distribution when your sample size tends to infinity. As long as your sample size is large enough, the average scores follow a normal distribution (Central Limit Theorem).

Upvotes: 0

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