by Craig Marker | Dec 24, 2006 | Uncategorized
In any experiment there is the possibility that extraneous variables, rather than the independent variable(s) are producing the change on the dependent variable (a confound or threat to internal validity). If the extraneous variable cannot be eliminated it must be...
by Craig Marker | Dec 23, 2006 | Uncategorized
In an earlier entry, I discussed types of correlation coefficients for variables with different scales of measurement. In this entry, I want to discuss correlation coefficients that are used with three or more variables. These coefficients are known as partial and...
by Craig Marker | Dec 22, 2006 | Uncategorized
One of the most confusing concepts in research is the distinction between mediators and moderators.A mediator ‘mediates’ the relationship between two variables (the independent and dependent variables). That is, the two variables are correlated, but their relationship...
by Craig Marker | Dec 22, 2006 | Uncategorized
There are many different ways to calculate how much two items are associated. The calculation of these correlation coefficients depend on how the items are measured. That is, the calculation depends in part on whether the items are measured on a nominal, ordinal,...
by Craig Marker | Dec 22, 2006 | Uncategorized
When you conduct a test of statistical significance, whether it is a t-test, correlation, an ANOVA, or regression, you are given a p-value in the output. Almost always, this p-value is for a two-tailed test.If you are using a significance level of .05, a two-tailed...
by Craig Marker | Dec 22, 2006 | Uncategorized
Mplus is becoming a commonly used statistical modeling program that is used for structural equation modeling. It has many unique features (e.g., easy syntax, item-response analysis, latent-class analysis, indirect effects calculations, and random coefficients) that...
by Craig Marker | Dec 22, 2006 | Uncategorized
An earlier post tried to clarify Type 1 and Type II errors. However, more clarification may be needed. Another way of thinking about Type I and Type II errors is to look at the experimenter’s conclusions.TYPE I ERRORIf the experimenter concludes that there was a...
by Craig Marker | Dec 22, 2006 | Uncategorized
One easily confused relationship is between Type I and Type II errors.A Type I error is when we reject the Null Hypothesis when in fact their was no effect (The Null Hypothesis always states that there is no relationship or no effect). That is, we conclude we found...
by Craig Marker | Dec 22, 2006 | Uncategorized
When looking at statistical databases, I have seen many elegant (and inelegant) methods of coding variables. One consistent coding question is how to code gender. Some people code 1 for male and 2 for female or the other way around. This means of coding leads to...
by Craig Marker | Dec 21, 2006 | Uncategorized
From TheOnion.com:Al Gore Caught Warming Globe To Increase Box Office ProfitsAl Gore Caught Warming Globe To Increase Box-Office Profits
