by David Lillis, Ph.D.

Last time we created two variables and used the lm() command to perform a least squares regression on them, and diagnosing our regression using the plot() command.

Just as we did last time, we perform the regression using lm(). This time we store it as an object M. [click to continue…]

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Linear Models in R: Diagnosing Our Regression Model

Last time we created two variables and used the lm() command to perform a least squares regression on them, treating one of them as the dependent variable and the other as the independent variable. Here they are again..

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Linear Models in R: Plotting Regression Lines

Today let’s re-create two variables and see how to plot them and include a regression line. We take height to be a variable that describes the heights (in cm) of ten people.

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Models for Repeated Measures Continuous, Categorical, and Count Data

Lately, I’ve gotten a lot of questions about learning how to run models for repeated measures data that isn’t continuous. Mostly categorical. But once in a while discrete counts. A typical study is in linguistics or psychology where..

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April 2015 Membership Webinar: Confidence Intervals

In this webinar we’ll clear up the ambiguity as to what exactly is a confidence interval and how to interpret them in a table and graph format..

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3 Tips for Keeping Track of Data Files in a Large Data Analysis

If you’ve ever worked on a large data analysis project, you know that just keeping track of everything is a battle in itself. Every data analysis project is unique, but here are a few strategies I used in a recent project that you may find helpful. They didn’t make the project easy, but they helped keep it from spiraling into overwhelm…

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Preparing Data for Analysis is (more than) Half the Battle

Just last week, a colleague mentioned that while he does a lot of study design these days, he no longer does much data analysis. His main reason was that 80% of the work in data analysis is preparing the data for analysis. Data preparation is s-l-o-w and he found that few colleagues and clients understood this…

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March 2015 Membership Webinar: Count Models

In this webinar, we’ll discuss the different model options for count data, including how to figure out which one works best. We’ll go into detail about how the models are set up, some key statistics, and how to interpret parameter estimates.

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Why Mixed Models are Harder in Repeated Measures Designs: G-Side and R-Side Modeling

I have recently worked with two clients who were running generalized linear mixed models in SPSS. Both had repeated measures experiments with a binary outcome. The details of the designs were quite different, of course. But both had pretty complicated combinations of within-subjects factors…

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Get your Sampling Out of My Survey Errors…

These types of errors are not associated with sample-to-sample variability but to sources like selection biases, frame coverage issues, and measurement errors. These are not the kind of errors you want in your survey.

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