Power and Sample Size

How Big of a Sample Size do you need for Factor Analysis?

Most of the time when we plan a sample size for a data set, it’s based on obtaining reasonable statistical power for a key analysis of that data set. These power calculations figure out how big a sample you need so that a certain width of a confidence interval or p-value will coincide with a scientifically meaningful effect size.

But that’s not the only issue in sample size, and not every statistical analysis uses p-values.

How Does the Distribution of a Population Impact the Confidence Interval?

by Jeff Meyer Leave a Comment

Spoiler alert, real data are seldom normally distributed.

How does the distribution influence the estimate of the population mean and the resulting confidence interval?

To figure this out, we randomly draw 100 observations 100 times from three distinct populations and plot the mean and corresponding 95% confidence interval of each sample.
[Read more…] about How Does the Distribution of a Population Impact the Confidence Interval?

Member Training: Interpretation of Effect Size Statistics

by guest

Effect size statistics are required by most journals and committees these days ⁠— for good reason.

They communicate just how big the effects are in your statistical results ⁠— something p-values can’t do.

But they’re only useful if you can choose the most appropriate one and if you can interpret it.

This can be hard in even simple statistical tests. But once you get into complicated models, it’s a whole new story. [Read more…] about Member Training: Interpretation of Effect Size Statistics

How Confident Are You About Confidence Intervals?

by Jeff Meyer 2 Comments

The results of any statistical analysis should include the confidence intervals for estimated parameters.

How confident are you that you can explain what they mean? Even those of us who have a solid understand of confidence intervals can get tripped up by the wording.

Let’s look at an example. [Read more…] about How Confident Are You About Confidence Intervals?

How to Interpret the Width of a Confidence Interval

by Christos Giannoulis 2 Comments

One issue with using tests of significance is that black and white cut-off points such as 5 percent or 1 percent may be difficult to justify.

Significance tests on their own do not provide much light about the nature or magnitude of any effect to which they apply.

One way of shedding more light on those issues is to use confidence intervals. Confidence intervals can be used in univariate, bivariate and multivariate analyses and meta-analytic studies.

Member Training: Power Analysis and Sample Size Determination Using Simulation

by guest Leave a Comment

This webinar will show you strategies and steps for using simulations to estimate sample size and power. You will learn:

A review of basic concepts of statistical power and effect size
A simulation-based approach to power analysis
An overview of how to implement simulations in various popular software programs.

[Read more…]