Analysis of Survey Data from Complex Sample Designs

Analysis of Survey Data from Complex Sample Designs

This course will teach you how to estimate variances for complex surveys and how to model the results using linear and logistic regression and other generalized linear models.

This course will teach you how to estimate descriptive quantities and sampling variances from complex surveys, and also how to fit linear and logistic regression models to complex sample survey data.

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Overview

Complex sample designs such as stratified cluster sampling make it possible to extract maximum information at minimum cost, but they are typically harder to work with than simple random samples. How do you analyze the resulting data – in particular, how do you determine margins of error? This course teaches you how to estimate variances when analyzing survey data from complex samples, and also how to fit linear and logistic regression models to complex sample survey data.
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Learning Outcomes

Students who complete this course will gain a basic understanding of applied survey data analysis and complex sample design. The course covers foundational statistics for finite populations and superpopulation models, descriptive statistics and a variety of regression models.

  • Fit regression models to complex sample survey data
  • Describe and classify different sample designs
  • Explain design-based estimation and inference
  • Analyze both continuous and categorical data from complex sample surveys

Who Should Take This Course

Anyone designing surveys or analyzing survey data.

Instructors

Mr. Brady .T. West

Dr. Brady T. West

Dr. Brady T. West is a Research Associate Professor in the Survey Research Center at the University of Michigan Institute for Social Research. His current research interests include survey nonresponse, interviewer variance, responsive and adaptive survey design, the analysis of complex sample survey data, and multilevel regression models for clustered and longitudinal data. He teaches several yearly short courses on statistical methodology and software, and is a lead or co-author on numerous publications presenting analyses of complex sample survey data.

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Course Syllabus

Week 1

Overview

  • Applied Survey Data Analysis: An Overview
  • Important terms, concepts, and notation
  • Software Overview
  • Getting to Know the Complex Sample Design
    • Classification of Sample Designs
    • Target Populations and Survey Populations
    • Simple Random Sampling
    • Complex Sample Design Effects
    • Complex Samples: Clustering and Stratification
    • Weighting in Analysis of Survey Data
    • Multi-stage Area Probability Sample Designs

Week 2

Overview Continued

  • Foundations and Techniques for Design-based Estimation and Inference
  • Finite Populations and Superpopulation Models
  • Confidence Intervals for Population Parameters
  • Weighted Estimation of Population Parameters
  • Probability Distributions and Design-based Inference
  • Variance Estimation
  • Hypothesis Testing in Survey Data Analysis
  • Total Survey Error
  • Preparation for Complex Sample Survey Data Analysis
    • Analysis Weights: Review by the Data User
    • Understanding and Checking the Sampling Error Calculation Model
    • Addressing Item Missing Data in Analysis Variables
    • Preparing to Analyze Data from Sample Subclasses
    • A Final Checklist for Data Users

Week 3

Descriptive Statistics

  • Descriptive Analysis for Continuous Variables
  • Special Considerations in Descriptive Analysis of Complex Sample Survey Data
  • Simple Statistics for Univariate Continuous Distributions
  • Bivariate Relationships between Two Continuous Variables
  • Descriptive Statistics for Subpopulations
  • Linear Functions of Descriptive Estimates and Differences of Means
  • Categorical Data Analysis
    • A Framework for Analysis of Categorical Survey Data
    • Univariate Analysis of Categorical Data
    • Bivariate Analysis of Categorical Data
    • Analysis of Multivariate Categorical Data

Week 4

Regression Models

  • Linear Regression Models
  • The Linear Regression Model
    • Fitting linear regression models to survey data
  • Four Steps in Linear Regression Analysis
  • Some Practical Considerations and Tools
  • Application: Modeling Diastolic Blood Pressure with the NHANES Data
  • Logistic Regression and Generalized Linear Models for Binary Survey Variables
    • Generalized Linear Models (GLMs) for Binary Survey Responses
    • Building the Logistic Regression Model: Stage 1-Model Specification
    • Building the Logistic Regression Model: Stage 2-Estimation of Model Parameters and Standard Errors
    • Building the Logistic Regression Model: Stage 3-Evaluation of the Fitted Model
    • Building the Logistic Regression Model: Stage 4-Interpretation and Inference
    • Analysis Application
    • Comparing the Logistic, Probit, and Complementary-Log-Log (C-L-L) GLMs for Binary Dependent Variables

Class Dates

2021

Oct 22, 2021 to Nov 19, 2021

2022

Oct 21, 2022 to Nov 18, 2022

2023

Oct 20, 2023 to Nov 17, 2023

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Prerequisites

You should have some familiarity with logistic regression, which is covered in several Institute courses (Logistic Regression, GLM, Categorical Data Analysis).  You should also be familiar with basic survey design and analysis, as covered in these courses:

Survey Analysis Course

Survey Analysis

This course will teach you how to analyze data gathered in surveys.
Topic: Statistics, Tests & Surveys | Skill: Introductory | Credit Options: CEU
Class Start Dates: Sep 23, 2022, Sep 22, 2023

What Our Students Say​

Stephen McAllister

The material covered here will be indispensable in my work. I can't wait to take other courses. Great work!

Stephen McAllister
Library Planning Consultant at Ottawa Public Library

I learned more in the past 6 weeks than I did taking a full semester of statistics in college, and 10 weeks of statistics in graduate school. Seriously.

Amir Aminimanizani
MRR Pharmacy Consulting, Inc

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We offer a “Student Satisfaction Guarantee​” that includes a tuition-back guarantee, so go ahead and take our courses risk free. That’s our commitment to student satisfaction. Students may cancel, transfer, or withdraw from a course under certain conditions. If you’re not satisfied with a course, you may withdraw from the course and receive a tuition refund.

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We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.

  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.

Please see this page for more information.

Who are the instructors at the Institute?

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  • Authors of well-regarded texts in their area;
  • Advisory board members;
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The majority of our instructors have more than five years of teaching experience online at the Institute.

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What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

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Our courses have several for-credit options:

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  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

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Related Courses

Survey Analysis Course

Survey Analysis

This course will teach you how to analyze data gathered in surveys.
Topic: Statistics, Tests & Surveys | Skill: Introductory | Credit Options: CEU
Class Start Dates: Sep 23, 2022, Sep 22, 2023

Additional Course Information

Organization of Course

This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

The homework in this course consists of short answer questions to test concepts, guided exercises in writing code and guided data analysis problems using software.

In addition to assigned readings, this course also has example software codes, supplemental readings available online, and an end of course data modeling project.

Course Text

The course text is Applied Survey Data Analysis 2nd Edition, by Steve Heeringa, Brady West, and Pat Berglund.

Please order a copy of your course textbook prior to course start date.

Software

The course will be driven by learning how to use specialized software procedures for the analysis of complex sample survey data, using real data sets, and exercises will be selected from the book chapters. Participants could use R, WesVar, or IVEware (free packages) or SAS, Stata, SUDAAN, or SPSS (commercial packages, with SPSS users required to purchase the Complex Samples Module). If you plan to use other software, check to be sure that it can analyze data from complex survey designs (clustered, stratified, multistage, etc.).

Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?” 

Course Fee & Information

Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

Supplemental Information

There is no supplemental content for this course.

Miscellaneous

There is no additional information for this course.

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Analysis of Survey Data from Complex Sample Designs
$589 | Enroll Now
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