Before and After Models in Observational Research Using Random Slopes and Intercepts
Source category: Analytics and Statistics
Author collections: David J. Pasta
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David J. Pasta — Indexed Papers
Publications credited to David J. Pasta in the available conference metadata. Browse coauthors and original source links below. This is a publication index, not a verified biographical profile; identical names may refer to different people.
26 papers · Showing 1–26
Beyond Breslow-Day: Homogeneity Across R x C Tables
Source category: Analytics and Statistics
Author collections: David R. Mink · David J. Pasta
Mix-and-Match: Mixed Models for Analyzing Binary Outcomes with Matched Samples
Source category: Health Outcomes and Healthcare Research Methodologies
Author collections: Sarah A. Short · David J. Pasta
The Last Shall Be First: Matching Patients by Choosing the Least Popular First
Source category: Health Outcomes and Healthcare Research Methodologies
Author collections: Stefanie J. Millar · David J. Pasta
Those Confounded Interactions: Building and Interpreting a Model with Many Potential Confounders and Interactions
Source category: Analytics and Statistics
Author collections: David J. Pasta
Evaluating the Change in Lung Function Over Time: Practicalities of Using ESTIMATE and CONTRAST Statements
Source category: Health Outcomes and Healthcare Research Methodologies
Author collections: David J. Pasta
Learning When To Be Discrete: Continuous vs. Categorical Predictors
Source category: Tutorials
Author collections: David J. Pasta
BFF: Binary Flags Forever (Or, Boole’s Paradise)
Source category: Analytics and Statistics
Author collections: David J. Pasta · Eric P. Elkin
Using Regression Diagnostics and Clustering Criteria to Uncover ID Errors
Source category: Analytics and Statistics
Author collections: David J. Pasta · Eric P. Elkin · Rory Michaelis
Characterizing Patterns of Longitudinal Data Completeness through Successive Refinement
Source category: Conference paper
Author collections: Lawrence Rasouliyan · David J. Pasta
Improving Your Graphics Using the SAS/GRAPH® Annotate Facility
Source category: Conference paper
Author collections: David R. Mink · David J. Pasta
Using Statistical Graphics to Understand Your Data (Not Just to Present Results)
Source category: Conference paper
Author collections: David J. Pasta
Characterizing Patterns of Longitudinal Data Completeness through Successive Refinement
Source category: Data Analysis and Statistics
Author collections: Lawrence Rasouliyan · David J. Pasta
Improving Your Graphics Using SAS/GRAPH Annotate Facility
Source category: Tutorials
Author collections: David J. Pasta · David R. Mink
Parameterizing Models to Test the Hypotheses You Want: Coding Indicator Variables and Modified Continuous Variables
Source category: Conference paper
Author collections: David J. Pasta
Using Statistical Graphics to Understand Your Data (Not Just Present Results)
Source category: Data Analysis and Statistics
Author collections: David J. Pasta
Creating Scales from Questionnaires: PROC VARCLUS vs. Factor Analysis
Source category: Conference paper
Author collections: David J. Pasta · Diana Suhr
Head of the CLASS: Impress Your Colleagues with a Superior Understanding of the CLASS Statement in PROC LOGISTIC
Source category: Conference paper
Author collections: David J. Pasta
Parameterizing Models to Test the Hypotheses You Want: Coding Indicator Variables and Modified Continuous Variables
Source category: Data Analysis and Statistics
Author collections: David J. Pasta
Estimating Standard Errors for CLASS Variables in Generalized Linear Models Using PROC IML
Source category: Conference paper
Author collections: David J. Pasta · Miriam G. Cisternas
Presenting Logistic Regression Models to Non-Statisticians: Adjusted Probabilities and Adjusted Risk Ratios
Source category: Data Analysis and Statistics
Author collections: David J. Pasta · Miriam G. Cisternas
Using Propensity Scores to Adjust for Group Differences: Examples Comparing Alternative Surgical Methods
Source category: Conference paper
Author collections: David J. Pasta
Estimating Standard Errors of Treatment Effects for Probit Models and for Linear Models of Log-Transformed Variables with PROC IML
Source category: Data Analysis and Statistics
Author collections: David J. Pasta · Miriam G. Cisternas · Cynthia L. Williamson
The Sums of Squares Are All the Same – How Can the LSMEANS Be So Different?
Source category: Data Analysis and Statistics
Author collections: Lori Potter · David J. Pasta
Exploratory Variable Clustering for Integrating Analyses
Source category: Statistics
Author collections: David J. Pasta · Lori Potter
The Intraclass Correlation: What Is It and Why Do We Care?
Source category: Statistics
Author collections: David J. Pasta