Power Analysis Help

We can help you with your projects involving Power Analysis.

Power Analysis is a largely misunderstood topic, and it causes anxiety to lots of people because it is a must for any serious statistical analysis, but lots of people do not really understand what statistical power is.

Power, in simple words, it is the probability of rejecting a false null hypothesis. What most people don't understand is that they try to find "the power" of a test, but in reality, power is a function, that depends on the true value of the parameter being tested.

People tend to set a value for the "effect size" in order to find the power, but they don't understand why this is so, or how to compute the effect size, or how can meta analysis help to find an estimate of effect size, when none is initially available.

We can guide you through the subtleties of conducting a valid power analysis. Typically, we use a piece of software called G-Power, but calculations could be done with other softwares.

How do you do a power analysis?

There are many ways to conduct a power analysis, and it all depends on the data and the context of your analysis.

For example, you may be planning to conduct a study, for which you will collect data, and you are interested in finding out what your sample size N should be in order for you study to have statistical power of 80%. In that case, you use a planned or a priori power analysis.

Another example is when you have conducted already your study, this is, the data have been collected and the data has been analyzed and you conclusions have been drawn. Then you call a statistics expert because you would like to know what is the observed power your conclusions have. For that you use an post-hoc or a-posteriori analysis.

What does power analysis help you ascertain?

Power analysis allows to determine you ability of detecting an existing effect. In slightly more technical terms, the statistical power is the probability of rejecting your null hypothesis, given that the null hypothesis is actually false.

In the jargon of hypothesis testing, the statistical power is \(1 - \beta\), where \(\beta\) is the probability of making a Type II error.

Conceptually speaking the idea of statistical power is easy, but the practical feat of estimating the statistical power for an actual study does require statistical expertise, and you will on the safer side by getting the help of a statistical consultant.

What does a power analysis of 80% mean?

A statistical power of .80, or 80% which is the same means that you have a probability of 80% of rejecting a false null hypothesis, or in other words, you have a probability of 80% of detecting an existing effect.

Normally, much attention is put on the probability of a Type I error, which is the probability of rejecting a true null hypothesis, which is typically set at the significance level of \(\alpha = 0.05\).

But then, little attention is often paid to the type II error. Having a relatively large power (80% and up is considered appropriate) ensures that you have a relatively low chance of making a type II error. Out statistical consultants at Sempax can help you with that.

Why Power Analysis Help is Advantageous for You?

Using expert power analysis assistance provides methodological rigor, allows you to make optimal use of resources, and it enhances your precision and detection capability, in order to produce more robust and trusted results that can hold up to scientific scrutiny.

• Statistical Power - Experts ensure your study has sufficient statistical power by calculating/confirming appropriate sample sizes.
• Precision - Power analysis maximizes the chance of detecting true effects and relationships in your data. Enhances accuracy.
• Efficiency - Optimized sample size saves time and resources from collecting non-impactful data.
• Trusted Results - Valid, properly powered studies provide credible, publishable findings less likely to be refuted later.