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Registeration for: Analysis of Survey Data from Complex Sample Designs
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Analysis of Survey Data from Complex Sample Designs
Category: PLANNING, RESEARCH AND STATISTICS COURSES

ABOUT THE COURSE:
In order to extract maximum information at minimum cost, sample designs are typically more complex than simple random samples. Cluster sampling and stratified designs are common. But how do you analyze the resulting data - in particular, how do you determine margins of error? This online course, "Analysis of Survey Data from Complex Sample Designs" 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.

COURSE CONTENT

MODULE 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
  • imple Random Sampling
  • Complex Sample Design Effects
  • Complex Samples: Clustering and Stratification
  • Weighting in Analysis of Survey Data
  • Multi-stage Area Probability Sample Designs

MODULE 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

MODULE 3: Descriptive Statistics

  • Descriptive Analysis for Continuous Variables
  • Special Considerations in Descriptive Analysis of Complex Sample Survey Data
  • Simple Statistics for Univariate Continuous Distruibutions
  • 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

MODULE 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

 

DATES:

02 May - 13 May, 2016,
18 Jul - 29 Jul, 2016,
12 Sep - 23 Sep, 2016,
14 Nov - 25 Nov, 2016

IMPORTANT NOTE:

FOR MORE DETAILS WITH RESPECT TO COURSE CONTENT E.T.C, PLEASE SEND YOUR REQUEST TO training@coinmac.org or call +2348023262908,+2348038437312
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