Survey data analysis using Stata

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Survey data analysis using Stata

Description

This course covers how to use Stata for survey data analysis assuming a fixed population. It begins by reviewing the sampling methods used to collect survey data, and then discusses how they act in the estimation of totals, ratios, and regression coefficients. It then covers variance estimation methods implemented in Stata’s survey estimation commands. The course will also cover strata with a single sampling unit, certainty sampling units, subpopulation estimation, and poststratification. Interactive Stata sessions are dispersed between lectures.

Price: $1,395

We offer a 15% discount for group enrollments of three or more participants.

Course leader

Chuck Huber is Director of Statistical Outreach at StataCorp LLC and Adjunct Associate Professor of Biostatistics at the Texas A&M School of Public Health and at the New York University School of Global Public Health. In addition to working with Stata's team of software developers, he produces instructional videos for the Stata YouTube channel, writes blog entries, develops online NetCourses, and gives talks about Stata at conferences and universities. Most of his current work is focused on statistical methods used by behavioral and health scientists. He has published in the areas of neurology, human and animal genetics, alcohol and drug abuse prevention, nutrition, and birth defects. Dr. Huber currently teaches survey sampling at NYU and introductory biostatistics at Texas A&M, where he previously taught categorical data analysis, survey data analysis, and statistical genetics.

Course topics

Sampling
Sampling design characteristics
- Cluster sampling
- Stratified sampling
- Sampling without replacement
Regression with survey data
Variance estimation
- Linearization
- Balanced repeated replication (BRR)
- Jackknife
- Bootstrap
- Successive difference replication (SDR)
Special types of sampling units
- Strata with a single sampling unit
- Certainty units
Restricted sample and subpopulation estimation
Poststratification

Learning outcomes

Attendees of this course will walk away with the following knowledge:

The difference between Stata’s standard estimation commands and svy estimation commands
How to create SRS and stratified samples from available lists
How to use Stata’s svyset command to identify the survey characteristics present in the dataset. These characteristics include:
- Sampling units at each sampling stage
- Strata at each sampling stage
- Sampling fractions used in the finite population correction when units are sampled with out replacement at each sampling stage
- Replication weight variables
- Poststrata and their associated sizes
How to handle certainty units
The available choices for handling strata with one sampling unit
The difference between restricted sample estimation and subpopulation estimation

Prerequisite

Knowledge of Stata is not required, but attendees are assumed to have some statistical knowledge, such as what is typically covered in an introductory statistics course. This course is geared toward data analysis professionals who are not familiar with the survey data features in Stata.

Next session

Currently, there are no scheduled sessions of this course.

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Notes

Enrollment is limited. This course may be offered in a classroom or web-based setting. The type (classroom or web-based) will be designated above when scheduled.

Classroom training courses are two-day courses that run from 8:30 a.m. to 4:30 p.m. each day. These courses take place at a training center where computers with Stata installed are provided. A continental breakfast, lunch, and an afternoon snack will also be provided.

Web-based training courses are four-day courses that run for three and a half hours each day. You will be provided with a temporary Stata license to install on your computer, a printed copy of the course notes, and all the course datasets so that you can easily follow along. Learn more about how our web-based training courses work, watch a video demonstration, and find technical requirements for participating in this type of training.

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