Soc 751: The workflow of data analysis (1st Summer Session 2013; May 7 orientation. May13-May 24: Lectures and labs. May 27-31: Independent work) This intensive class deals with the entire process of research: planning, documenting, and organizing your work; creating, labeling, naming, and verifying variables; performing and presenting statistical analyses; preserving your work; and, critically, producing replicable results. Most classes in statistics focus on estimating and interpreting models. In "real world" research, these activities often involve less than 10% of the total work. This workshop is about the other 90% of the work. Contact Scott Long for authorization to enroll. 25Feb2013
ICPSR Summer Program Workshop on The Workflow of Data Analysis using Stata: June 17-21, 2013 at the Center for Research on Families at the University of Massachusetts-Amherst. For details, check here. Contact Scott Long if you have questions. 25Feb2013
ICPSR Summer Program Workshop on Models for Categorical Outcomes Using Stata: July 8-12, 2013 at the University of Michigan-Ann Arbor. For further details, check here. Contact Scott Long if you have questions. 25Feb2013
Soc 651 Multivariate Analysis: Spring 2013. This class deals with techniques referred to broadly as multivariate methods. The class focuses on how thse methods can be used to take multiple variables and extract a smaller number of more useful measures. Examples include: multiple tests scores used to create a single scale of ability; using indicators of exposure to cultural events to create a measure of cultural capital; using a series of questions about social distance from a person with a mental illness to create a single measure of social distances. This is often a critical first step in analyzing survey data. Specific methods to be considered include cluster analysis, multidimensional scaling, principal components analysis, and variations of the factor model such as exploratory factor analysis, confirmatory factor analysis, latent class analysis, item response models, and SEM. Prerequisites: Students need a prior course on the linear regression model and a course on models for categorical outcomes.
CDA at IU: Stat 503 and Soc 650: Categorical Data Analysis is a second course in applied regression model that is normally taught Fall Semester. This course assumes a prior course, such as Soc 554 or Stat 501, that deals with models for dependent variable that are continuous. These include the linear regression model, seemingly unrelated regressions, and systems of simultaneous equations. Soc 650 and Stat 503 deals with regression models in which the dependent variable is categorical. Such models include probit and logit for binary outcomes, ordered logit and ordered probit for ordinal outcomes, multinomial logit for nominal outcomes, and Poisson regression and related models for count outcomes. The prerequisite for this class is a prior course in regression. The class uses Stata. Sometimes there are more students who want to take this class than there are seats in the class; for enrollment information click here.