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February 2018

Introduction to Statistical Software

February 7 @ 2:00 pm - 4:00 pm

Introduction to Statistical Software:  Wednesday, Februray 7 from 2 to 4 p.m. in the Research Commons classroom (RC), Charles E. Young Research Library Description:  This hands-on workshop will introduce some commonly used statistical software packages, including R, SAS, SPSS and Stata.  Sign up at http://www.library.ucla.edu/support/research-help/attend-research-workshop/advanced-research-workshop-series-0 .

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Introduction to Mplus 8

February 12 @ 9:00 am - 12:00 pm

Introduction to Mplus 8:  Monday, February 12 from 9 a.m. to 12 noon in the Visualization Portal, Math Science 5628 Description: Mplus is a powerful statistical package used for the analysis of both observed and latent variables. Among the kinds of analysis it can perform are exploratory factor analysis, confirmatory factor analysis, latent class analysis, latent growth curve modeling, structural equation modeling and multilevel modeling. This workshop is designed for people who are just getting started using Mplus. Our aim…

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Consulting closed

February 19
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Extended Regression Models in Stata 15

February 22 @ 12:00 pm - 2:00 pm

This talk will be presented by Chuck Huber from Stata Corp. Abstract: Observational data often have issues which present challenges for the data analyst. The treatment status or exposure of interest is often not assigned randomly. Data are sometimes missing not at random (MNAR) which can lead to sample selection bias. And many statistical models for these data must account for unobserved confounding. This talk will demonstrate how to use standard maximum likelihood estimation to fit extended regression models (ERMs)…

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Using the MIXED command in SPSS

February 26 @ 9:00 am - 12:00 pm

Using the MIXED command in SPSS:  Monday, February 26 from 9 a.m. to 12 noon in the Visualization Portal, Math Science 5628 Description:   This seminar will illustrate the different kinds of models that can be run with the SPSS command MIXED.  Basic syntax and useful options will be discussed, as well as possible solutions to common problems encountered in multilevel modeling.  Examples of both two- and three-level models will be provided.  Sign up at https://idre.ucla.edu/calendar-event/using-mixed-command-spss only if you are able to…

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March 2018

Data Management in R

March 5 @ 9:00 am - 12:00 pm

Data Management in R:  Monday, March 5 from 9 a.m. to 12 noon in the Visualization Portal, Math Science 5628 Description: This seminar introduces R packages and functions that help users import, transform and manage their data in preparation for analysis.   The seminar focuses on the “tidy data” philosophy encouraged by the “tidyverse” collection of R packages, but draws on other packages for useful functions as needed.  Topics include data import, transforming variables, string functions, missing data, merging datasets, reshaping…

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Consulting closed

March 19 - March 23
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Structural Equation Modeling (SEM) Foundations Seminar

March 26 @ 8:30 am - March 28 @ 5:30 pm

IDRE Statistical Consulting, together with Stats Camp, is excited to announce a 3-day Structural Equation Modeling training seminar, led by Dr. Todd D. Little, March 26-28 here at UCLA. IDRE has formed a new partnership with Stats Camp (https://www.statscamp.org/), an award-winning organization that provides statistical/data analysis seminars at a graduate and post-graduate level. This partnership has allowed us to offer a substantial 35% discount on registration fees, exclusive to UCLA researchers for this March event only! Despite training in the…

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April 2018

walk-in consulting opening at 1:30 p.m.

April 18 @ 1:30 pm - 3:00 pm
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May 2018

Logistic Regression in SAS

May 7 @ 9:00 am - 12:00 pm

You can sign up here . Title:  Logistic Regression in SAS Date:  May 7, 2018 Time:  9 a.m. to 12 noon Location:  5628 Math Sciences (Visualization Portal) Description:  This workshop will cover modeling binary outcome with logistic regression in SAS. We will discuss the logistic regression model, model building and fitting, interpretation of estimated parameters, assessment of model fit, graphing of model effects, and ROC analysis.  This workshop does NOT cover ordinal or multinomial logistic regression.

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