Quantitative Methods

Quantitative Social Research Methods courses provide rigorous training for researchers and professionals on disciplines data science, design such as descriptive, correlation, quasi-experimental, experimental and more. Courses here are available as aids to all fields of research and professions, giving practical and comprehensible knowledge as well as the most up to date methods.



Longitudinal Data Analysis Using Stata | 02/20 – 02/21

This course examines each of methods in some detail, with an eye to discerning their relative advantages and disadvantages. This is a hands-on course with ample opportunity for participants to practice the different methods. The two day course is joint hosted by Statistical Horizons and Metrika Consulting and will be taught by Dr. Paul Allison.

Survival Analysis Using Stata | 02/22 – 02/23

Survival methods are explicitly designed to deal with censoring and time-dependent covariates in a statistically correct way. Survival Analysis covers both the theory and practice of survival methodology. Assuming no previous knowledge of survival analysis, this course will turn you into a knowledgeable and skilled user of these indispensable techniques. This is part of the Mtrika Strata Winter School.

Latent Growth Curve Modeling | 04/27-04/28

Two-day seminar hosted by Statistical Horizons in April will provide a thorough introduction to latent growth curve models, which facilitate an assessment of longitudinal change from within the structural equation modeling framework. The seminar is taught by Dr. Gregory Hancock and will review SEM with measured and latent variables as well as introduce and illustrate Mplus. The seminar will then review more traditional longitudinal models within an SEM framework to finish laying the necessary foundations.

Multilevel Modeling | 04/06-04/07

This two-day seminar from host Statistical Horizons provides a thorough introduction to multilevel modeling, a statistical framework that accounts for the nesting effect and avoids these problems, as well as those associated with earlier methods of aggregation and dis-aggregation.

Longitudinal Data Analysis Using SEM | 05/17-05/18

This seminar is designed for those who want to analyze longitudinal data with three or more time points, and whose primary interest is in the effect of predictors that vary over time. You should have a solid understanding of basic principles of statistical inference, including such concepts as bias, sampling distributions, standard errors, confidence intervals, and hypothesis testing. You should also have a good working knowledge of the principles and practice of linear regression.

Multilevel Modeling of Non-Normal Data | 06/07-06/08

This workshop will focus on analysis of dichotomous, ordinal and nominal multilevel outcomes. Both clustered and longitudinal data will be considered, and the following models will be described: multilevel logistic regression for dichotomous outcomes, multilevel logistic regression for nominal outcomes, and multilevel proportional odds and non-proportional odds models for ordinal outcomes.

Longitudinal Data Analysis Using Stata | 06/15-06/16

In this seminar, you will learn how to do regression analysis of panel data—the most common type of longitudinal data. Panel data contain measurements of predictor and response variables at two or more points in time for many individuals. Although panel data have many attractions, the downside is that repeated measurements typically violate assumptions of independence.

Structural Equation Modeling | 07/16-07/20

This 5-day seminar hosted by Statistical Horizons starting July 16 at 9 is designed to make you a knowledgeable, effective and confident user of methods for structural equation modeling. Dr. Paul Allison will include 1 to 2 hours of supervised, practical exercises that will help you achieve mastery of these methods.