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Multilevel/Mixed Models Using Stata

Description

This two-day course is an introduction to using Stata to fit multilevel/mixed models. Mixed models contain both fixed effects analogous to the coefficients in standard regression models and random effects not directly estimated but instead summarized through the unique elements of their variance–covariance matrix. Mixed models may contain more than one level of nested random effects, and hence, these models are also referred to as multilevel or hierarchical models, particularly in the social sciences. Stata’s approach to linear mixed models is to assign random effects to independent panels where a hierarchy of nested panels can be defined for handling nested random effects.

The course will be interactive, use real data, and offer ample opportunity for specific research questions and for working exercises to reinforce what is learned.

The course will be taught in five parts. During the first four parts, the discussion will be confined to linear mixed models for continuous responses. The fifth part will focus on binary and count responses.

Price: $1,295  

We offer a 15% discount for group enrollments of three or more participants. Please contact us at training@stata.com for details.

Course topics

Prerequisite

Basic knowledge of standard linear regression and a working knowledge of Stata and the Do-file Editor.

Next session

Course Dates Location Cost Enroll
Multilevel/Mixed Models Using Stata October 9–10, 2014
Washington, DC
$1,295 Enroll

Email training@stata.com to request to be notified of future training sessions.

Notes

Enrollment is limited. Computers with Stata installed are provided at all public training sessions. All training courses run from 8:30 a.m. to 4:30 p.m. each day. A continental breakfast, lunch, and an afternoon snack will also be provided; the breakfast is available before the course begins. All participants are encouraged to bring a USB flash drive to all public training sessions; this is the safest and simplest way to save your work from the session.

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