Predicting future outcomes, the next steps in a process, or the best choice(s) from an array of possibilities are all essential needs in many fields. The predictive model is used as a decision making tool in advertising and marketing, meteorology, economics, insurance, health care, engineering, and would probably be useful in your work too! (more…)
Stage 3
Member Training: A Predictive Modeling Primer: Regression and Beyond
May 31st, 2019 by guest contributer
Member Training: Multiple Imputation for Missing Data
May 6th, 2019 by Jeff Meyer
There are a number of simplistic methods available for tackling the problem of missing data. Unfortunately there is a very high likelihood that each of these simplistic methods introduces bias into our model results.
Multiple imputation is considered to be the superior method of working with missing data. It eliminates the bias introduced by the simplistic methods in many missing data situations.
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What Is a Hazard Function in Survival Analysis?
April 29th, 2019 by Karen Grace-Martin
One of the key concepts in Survival Analysis is the Hazard Function.
But like a lot of concepts in Survival Analysis, the concept of “hazard” is similar, but not exactly the same as, its meaning in everyday English. Since it’s so important, though, let’s take a look. (more…)
Member Training: Meta-analysis
October 31st, 2018 by guest contributer
Meta-analysis is the quantitative pooling of data from multiple studies. Meta-analysis done well has many strengths, including statistical power, precision in effect size estimates, and providing a summary of individual studies.
But not all meta-analyses are done well. The three threats to the validity of a meta-analytic finding are heterogeneity of study results, publication bias, and poor individual study quality.
Member Training: Latent Growth Curve Models
October 1st, 2018 by Jeff Meyer
What statistical model would you use for longitudinal data to analyze between-subject differences with within-subject change?
Most analysts would respond, “a mixed model,” but have you ever heard of latent growth curves? How about latent trajectories, latent curves, growth curves, or time paths, which are other names for the same approach?
Member Training: Generalized Linear Models
September 3rd, 2018 by guest contributer
In this webinar, we will provide an overview of generalized linear models. You may already be using them (perhaps without knowing it!).
For example, logistic regression is a type of generalized linear model that many people are already familiar with. Alternatively, maybe you’re not using them yet and you are just beginning to understand when they might be useful to you.