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Which of the following describes the effect of increasing sample size in a repeated measure design?

Which of the following describes the effect of increasing sample size in a repeated-measures design? There is little or no effect on measures of effect size, but the likelihood of rejecting the null hypothesis increases.

Which of the following describes the effect of increasing sample size quizlet?

If other factors are held constant, what is the effect of increasing the sample size? It will increase the estimated standard error and decrease the likelihood of rejecting H0. Using an independent-measures t, the 90% confidence interval for the difference between two population means ranges from 19 to 23.

Which of the following is a concern when using a repeated measures design?

Repeated measures designs have some disadvantages compared to designs that have independent groups. The biggest drawbacks are known as order effects, and they are caused by exposing the subjects to multiple treatments. Order effects are related to the order that treatments are given but not due to the treatment itself.

What is the effect of an increase in the variance for the sample of difference scores?

Increasing the variance of each sample will increase the size of the estimated standard error of the difference of the means. This decreases the size of the observer t which makes it harder to reject H0. In other words, increased within-group variability decreases statistical power.