Analytic Methods in Maternal and Child Health
Enhancing Analytic Capacity in State Health Agencies through Competency-Based Education Arden Handler, DrPH
Epidemiology and Biostatistics, Modules 1, 2, and 3: Introduction
Module 1: Descriptive Epidemiology and Statistical Estimation Deborah Rosenberg, PhD and Arden Handler, DrPH
Epidemiologic Concepts 3
Person, Place, and Time Characteristics 4
Person Characteristics 4
Place Characteristics 7
Time Characteristics 7
Statistics Used in Public Health 10
Types of Variables 10
Means and Proportions 12
Rates 15
Prevalence and Incidence 18
Choosing Statistics to Report 22
Defining Categories 25
The Sampling Framework 29
Evaluating the Accuracy of Statistics 32
The Mean and Variance of Probability Distributions 34
Means and Variances for Means, Proportions, and Rates 34
The Central Limit Theorem 39
Confidence Intervals 39
Choosing the Best Estimates 43
The Epidemiologic View of Best Estimates 43
Biases Due to Collecting Information from a Select Population 44
Biases Due to Measurement of Information 44
Module 2: Measures of Association and Hypothesis Testing Deborah Rosenberg, PhD and Arden Handler, DrPH
Measures of Association: Difference Measures 48
Two Independent Means 48
Two Independent Proportions 50
The Attributable Risk 56
Hypotheses about a Mean, Proportion, or Rate in Comparison to a Standard 61
Measures of Association: Ratio Measures 63
The Relative Risk, the Relative Prevalence, and the Odds Ratio 63
The Preventive Fraction 71
Ecologic Analysis 73
Final Notes on Interpreting 2×2 Tables 74
Module 3: Analytic Epidemiology and Multivariable Methods Deborah Rosenberg, PhD and Arden Handler, DrPH
Research Designs in Analytic Epidemiology 77
Cohort Study 78
Case-Control Study 79
Data from the Entire Population 79
Ecologic Designs 80
Designs for Program Evaluation 81
Choosing a Study Design 81
Adjustment for Confounding 86
Steps in Evaluating Confounding Based on Analysis of 2×2 Tables 87
Evaluating Effect Modification Based on Analysis of 2×2 Tables 88
Confounding and Standardization of Rates 92
Direct Standardization 95
Indirect Standardization 95
Synthetic Estimation 100
Overview of Multivariable Regression Methods 104
Epidemiology and Biostatistics: Exercises and Solutions 115
References for Epidemiology and Biostatistics 135
Module 4: Methods for Summarizing Data Deborah Rosenberg, PhD
Developing an Analysis Plan 137
Purpose of the Analysis 138
The Audience for the Analysis 139
Availability of Data and Data Quality 139
Variables, Methods, and Presentation 140
Methods for Increasing Interpretability 143
Categorization 143
Integer Ranking 147
Percentile Rescaling 148
Z-Scores 153
Z-Tests 157
Index Construction 163
Summarizing Data to Allocate Resources 168
Methods for Summarizing Data: Exercises and Solutions 173
Module 5: Methods for Analyzing Trend Data Deborah Rosenberg, PhD
Why Do Trend Analysis? 194
Preparing to Analyze Trend Data 195
Analysis of Trend Data 199
Data Transformation and Smoothing 203
Reporting Average Annual Percent Change in an Indicator 205
Statistical Procedures 207
Chi-Square Test for Linear Trend 207
Regression Analysis 208
Other Considerations When Selecting Graphing or Statistical Approaches 215
Trend Analysis and Use of Local, State, or National Objectives 219
Presentation of Trend Data 220
Summary 221
Technical Note on Confidence Bands and Confidence Limits 222
Methods for Analyzing Trend Data: Exercises and Solutions 225
Selected Bibliography for Methods for Analyzing Trend Data 229
Module 6: Creating Target Population Estimates Using National Survey Data Colleen Monahan, DC, MPH
Describing Target Population Characteristics for Children with Special Health Care Needs 233
Who Are Children with Special Health Care Needs? 234
Diagnosis-Based Approach 235
Function-Based Approach 235
Service-Based Approach 236
Classification Systems for Disability 236
The National Advisory Board on Medical Rehabilitation Research Model 236
International Classification of Impairment, Disabilities, and Handicaps (ICIDH)237
Institute of Medicine/Saad Nagi Model 237
Other Models or Definitions of Disability 237
Framework Proposed by Ruth Stein, et al for the QuiCC 237
National Association of Children's Hospitals and Related Institutions (NACHRI)
Classification System 238
Definition from the Federal Bureau of Maternal and Child Health 238
Definition Using State Program Eligibility 239
Americans with Disabilities Act (ADA) 239
The Physical-Mental Continuum 239
The Role of Sociodemographic Factors in Estimating Disability 240
Sources of Data on Disability 240
The Census Bureau 240
The National Center for Health Statistics 240
Using National Data to Develop Synthetic Estimates 243
Creating a Synthetic Estimate 243
Potential Biases Associated with Creating Synthetic Estimates 244
Creating Target Population Estimates Using National Survey Data: Exercises
and Solutions 246
References for Creating Target Population Estimates Using National Survey Data 256
Module 7: Using Census Data in MCH Colleen Monahan, DC, MPH
Description of the Census 258
History of the Census 258
The Evolution of the Census 259
The 1990 Census 259
Census in the Year 2000 260
The Modern Census 260
Census Content and Sample Design 261
Short Form 261
Long Form 261
Census Geography 263
Dissemination of Census Products 264
Printed Reports 264
Computer Tapes 265
Summary Tape Files (STFs) 265
Main Features of Summary Tape Files 265
Public Use of Microdata Samples (PUMs) 265
Other Special Computer Tape Files 266
Microfiche 266
CD-ROM 266
Special Tabulations 266
Online Services 266
Maps and Geographic Files 267
Machine-Readable Geographic Files 267
Using Census Data for Demographic and Socioeconomic Analysis 267
Demographics 267
Socioeconomic Data 268
Socioeconomic Indicators 269
Summary of Technical Issues for Calculating Totals and Percents Using Census Data 270
Summary of Commonly Used Formulae 271
Index 277