Interpreting the results of logistic regression can be tricky, even for people who are familiar with performing different kinds of statistical analyses. How do we then share these results with non-researchers in a way that makes sense?

## Latest Blog Posts

Whenever you use a multi-item scale to measure a construct, a key step is to create a score for each subject in the data set. This score is an estimate of the value of the latent construct (factor) the scale is measuring for each subject. In fact, calculating this score is the final step of […]

We all want rules of thumb even though we know they can be wrong, misleading or misinterpreted. Rules of Thumb are like Urban Myths or like a bad game of ‘Telephone’. The actual message gets totally distorted over time. For example, you may have heard this one: “The Chi-Square test is invalid if we have […]

An extremely useful area of statistics is a set of models that use latent variables: variables whole values we can’t measure directly, but instead have to infer from others. These latent variables can be unknown groups, unknown numerical values, or unknown patterns in trajectories.

Repeated measures is one of those terms in statistics that sounds like it could apply to many situations. In fact, it describes only one specific situation. A repeated measures design is one where each subject is measured repeatedly over time, space, or condition on the dependent variable. These repeated measurements on the same subject are […]

Data Cleaning is a critically important part of any data analysis. Without properly prepared data, the analysis will yield inaccurate results. Correcting errors later in the analysis adds to the time, effort, and cost of the project.

No, a degree of freedom is not “one foot out the door”! Definitions are rarely very good at explaining the meaning of something. At least not in statistics. Degrees of freedom: “the number of independent values or quantities which can be assigned to a statistical distribution”. This is no exception.

The Kappa Statistic or Cohen’s* Kappa is a statistical measure of inter-rater reliability for categorical variables. In fact, it’s almost synonymous with inter-rater reliability. Kappa is used when two raters both apply a criterion based on a tool to assess whether or not some condition occurs. Examples include:

In the world of statistical analyses, there are many tests and methods that for categorical data. Many become extremely complex, especially as the number of variables increases. But sometimes we need an analysis for only one or two categorical variables at a time. When that is the case, one of these seven fundamental tests may […]

When you are taking statistics classes, there is a lot going on. You’re learning concepts, vocabulary, and some really crazy notation. And probably a software package on top of that. In other words, you’re learning a lot of hard stuff all at once. Good statistics professors and textbook authors know that learning comes in stages. […]