Statistics How To

Regression Analysis > Chow Test What is a Chow Test The Chow test tells you if the regression coefficients are different for split data sets. Basically, it tests whether one regression line or two separate regression lines best fit a split set of data. Split Data Sets and the Chow Test Sometimes your data will … Read more

Statistics Definitions > Dimensionality What is Dimensionality? Dimensionality in statistics refers to how many attributes a dataset has. For example, healthcare data is notorious for having vast amounts of variables (e.g. blood pressure, weight, cholesterol level). In an ideal world, this data could be represented in a spreadsheet, with one column representing each dimension. In … Read more

Multivariate Analysis > Pillai’s Trace What is Pillai’s Trace? Pillai’s trace is used as a test statistic in MANOVA and MANCOVA. This is a positive valued statistic ranging from 0 to 1. Increasing values means that effects are contributing more to the model; you should reject the null hypothesis for large values. Pillai’s is one … Read more

Statistics Definitions > Roy’s Largest Root is a positive-valued, multivariate test statistic obtained in a hypothesis test. The test, along with similar statistics (e.g. Wilks’ Lambda or Pillai’s Trace) rely on eigenvalues. Where Roy’s Largest Root differs is that the focus is on extreme eigenvalues: It is the largest eigenvalue in a generated test matrix. … Read more

Regression Analysis > What is the Probit Model? A probit model (also called probit regression), is a way to perform regression for binary outcome variables. Binary outcome variables are dependent variables with two possibilities, like yes/no, positive test result/negative test result or single/not single. The word “probit” is a combination of the words probability and … Read more

Regression Analysis > Poisson Regression What is Poisson Regression? Poisson regression is used to model response variables (Y-values) that are counts. It tells you which explanatory variables have a statistically significant effect on the response variable. In other words, it tells you which X-values work on the Y-value. It’s best used for rare events, as … Read more

Hypothesis Testing > Wald Test What is the Wald Test? The Wald test (also called the Wald Chi-Squared Test) is a way to find out if explanatory variables in a model are significant. “Significant” means that they add something to the model; variables that add nothing can be deleted without affecting the model in any … Read more

Familywise Error Rates > Holm-Bonferroni Method You may want to read this article first: Familywise Error Rates. What is the Holm-Bonferroni Method? The Holm-Bonferroni Method (also called Holm’s Sequential Bonferroni Procedure) is a way to deal with familywise error rates (FWER) for multiple hypothesis tests. It is a modification of the Bonferroni correction. The Bonferroni … Read more

Unidimensionality > Guttman Scale What is the Guttman Scale? In the social sciences, the Guttman or “cumulative” scale measures how much of a positive or negative attitude a person has towards a particular topic. The Guttman scale is one of the three major types of unidimensional measurement scales. The other two are the Likert Scale … Read more

Bias > Measurement Error What is Measurement Error? Measurement Error (also called Observational Error) is the difference between a measured quantity and its true value. It includes random error (naturally occurring errors that are to be expected with any experiment) and systematic error (caused by a mis-calibrated instrument that affects all measurements). For example, let’s … Read more