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Latest Blog Posts

September Member Training: Inference and p-values and Statistical Significance, Oh My!

September 1, 2020

Statistical inference using hypothesis testing is ubiquitous in science. Several misconceptions and misinterpretations of p-values have arisen over the years, which can lead to challenges communicating the correct interpretation of results.

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

August 21, 2020

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 […]

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Effect Size Statistics: How to Calculate the Odds Ratio from a Chi-Square Cross-tabulation Table

August 12, 2020

Lest you believe that odds ratios are merely the domain of logistic regression, I’m here to tell you it’s not true. One of the simplest ways to calculate an odds ratio is from a cross tabulation table. We usually analyze these tables with a categorical statistical test. There are a few options, depending on the […]

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Member Training: Explaining Logistic Regression Results to Non-Researchers

August 1, 2020

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?

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Why Adding Values on a Scale Can Lead to Measurement Error

July 22, 2020

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 […]

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Chi-Square Test of Independence Rule of Thumb: n > 5

July 15, 2020

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 […]

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Member Training: A Guide to Latent Variable Models

July 1, 2020

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.

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Three Designs that Look Like Repeated Measures, But Aren’t

June 19, 2020

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 […]

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Member Training: Data Cleaning

June 1, 2020

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.

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What is a Degree of Freedom?

May 27, 2020

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.

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