Regression is one of the most common analyses in statistics. Most of us learn it in grad school, and we learned it in a specific software. Maybe SPSS, ... Continue Reading
Regression is one of the most common analyses in statistics. Most of us learn it in grad school, and we learned it in a specific software. Maybe SPSS, ... Continue Reading
The objective for quasi-experimental designs is to establish cause and effect relationships between the dependent and independent variables. However, ... Continue Reading
Do you ever wish your data analysis project were a little more organized? ... Continue Reading
Interactions in statistical models are never especially easy to interpret. Throw in non-normal outcome variables and non-linear prediction functions ... Continue Reading
Most survival analysis models for time-to-event data, like Cox regression, assume independence. The survival time for one individual cannot influence ... Continue Reading
How do you know which method to use when you want to compare groups? ... Continue Reading
One of the hardest steps in any project is learning to ask the right research question! ... Continue Reading
What do you do if the assumptions of linear models are violated? ... Continue Reading
Exact and randomization tests are simple from a conceptual level and need fewer assumptions than traditional parametric tests. They do require ... Continue Reading
Interactions in statistical models are never especially easy to interpret. Throw in non-normal outcome variables and non-linear prediction functions ... Continue Reading
Many data sets are challenging and time consuming to work with because the data are seldom in an optimal format. ... Continue Reading
Moderated mediation, also known as Conditional Process Modeling, is great tool for understanding one type of complex relationship among variables. ... Continue Reading
If you’ve used much analysis of variance (ANOVA), you’ve probably heard that ANOVA is a special case of linear regression. Unless you’ve seen why, ... Continue Reading
Multinomial logistic regression is an important type of categorical data analysis. Specifically, it's used when your response variable is nominal: ... Continue Reading
Centering variables is common practice in some areas, and rarely seen in others. That being the case, it isn’t always clear what are the reasons for ... Continue Reading
Multilevel and Mixed models are essentially the same analysis. But they use different vocabulary, different notation, and approach the analysis ... Continue Reading
In this 8-part tutorial, you will learn how to get started using Stata for data preparation, analysis, and graphing. This tutorial will give you the ... Continue Reading
Is it really ok to treat Likert items as continuous? And can you just decide to combine Likert items to make a scale? Likert-type data is extremely ... Continue Reading
Bootstrapping is a methodology derived by Bradley Efron in the 1980s that provides a reasonable approximation to the sampling distribution of various ... Continue Reading
What are the assumptions of linear models? If you compare two lists of assumptions, most of the time they're not the same. ... Continue Reading
structural equation modeling resources Listed below are workshops, trainings, and articles to help you learn Structural Equation Modeling (SEM). SEM ... Continue Reading
principal component analysis and factor analysis resources Listed below are workshops, trainings, and articles to help you learn principal component ... Continue Reading
survival analysis and event history analysis resources Listed below are workshops, trainings, and articles to help you learn survival analysis, ... Continue Reading
count regression models resources Like continuous variables, count variable are numerical. So it seems you should be able to apply methods for ... Continue Reading
logistic regression resources Listed below are workshops, trainings, and articles to help you learn logistic regression. Logistic regression is an ... Continue Reading
mixed and multilevel models resources Listed below are workshops, trainings, and articles to help you learn Mixed, Hierarchical, and Multilevel ... Continue Reading
linear regression resources Listed below are workshops, trainings, and articles to help you learn linear regression. Widely used, this family of ... Continue Reading
analysis of variance and covariance resources Listed below are workshops, trainings, and articles to help you learn Analysis of Variance (ANOVA) and ... Continue Reading
Levels of Measurement and Types of Variables Training Seminar Understand the nuances in determining the types of variables you're working with and ... Continue Reading
Types of Regression Models: Training Seminar 18 Types of Regression Models — What They Are and When to Use Them Enroll Now! Linear, Logistic, ... Continue Reading
Crossed and Nested Factors Training Seminar Understand the difference between crossed and nested factors in multilevel, mixed models, and ... Continue Reading
effect size statistics, power and sample calculations, and statistical inference Use these resources to learn with The Analysis Factor. Listed below ... Continue Reading
how can The Analysis Factor help you with statistics? ... Continue Reading
resources for fundamental statistics Use the resources here to learn fundamental statistics with The Analysis Factor. Listed Below are our Workshop, ... Continue Reading
Resources to improve your data analysis practice and skills As a data analyst, it's not enough to understand statistics or to be able to use the ... Continue Reading
complex surveys & sampling resources Listed below are workshops, trainings, and articles to help you learn about complex surveys. Complex surveys ... Continue Reading
effect size statistics, power and sample calculations, and statistical inference Listed below are our free webinars, Statistically Speaking ... Continue Reading