Biostatistics Consultation Core
How to Impute and Analyze Missing Data Using… SAS, R, Stata SPSS and REDCap
Wednesday, Mar. 29 at 11 a.m.
Missing data is a common issue for researchers who carry out any type of quantitative analysis, whether based on primary or secondary data. While the amount of missing can be minimized in the study design phase, it cannot be completely eliminated. This How-to webinar will introduce the issue of missing data—distinguishing between unit non-response and item non-response—and the multiple imputations approach, a practical solution for dealing with missing data. The webinar will show how to implement multiple imputations using different software (Stata, R, SAS, and SPSS).
How to Jointly Analyze Longitudinal Data and Time-to-Dropout or Time-to-Death Simultaneously; An Integrative Data Harmonization Approach
Monday, Apr. 24 at 10 a.m.
Drawing on theory and prior research, evidence-based research can generate data from different sources and phases of research. A central feature of evidence-based research is the sequential and longitudinal implementation of data analysis allowing research participants to be removed for various study related end-points throughout the research timeline. This How-to seminar is to primarily give an overview of pitfalls in longitudinal data analysis and further discuss an integrative data harmonization with joint modeling of longitudinal data and time-to-event (such as dropout and censored) data simultaneously using real data from a HIV/AIDS clinical trial. We demonstrate that an integrative data harmonization has the potential to produce a more efficient and more powerful statistical analysis.
How to Do Structural Equation Modeling Using… SAS, R & MPlus, Stata and SPSS
Wednesday, Feb. 22 at 11 a.m.
Structural Equation Modeling (SEM) is a statistical technique that is capable of modeling complex relationships among multiple independent and dependent variables. This approach is especially useful when describing the interrelationships of variables comprising ecosystem-like phenomena, such as recursive and mediating relationships. This How-to webinar will introduce the basic principles of SEM and review approaches to coding SEM in various statistical programs.
How to Validate Survey Measurement Models with EFA/CFA Using… SAS, R, Stata and SPSS
Monday, Jan. 30 at 10 a.m.
Reporting empirical evidence that an instrument measures what it purports to measure gives us confidence that results are valid. Thus, developing and validating survey measurements using Exploratory and/or Confirmatory Factor Analysis reduces bias in the interpretation of results. This webinar will focus on conducting factor analysis to validate survey measurement models using 4 different statistical software packages (R, STATA, SAS, and SPSS).
How to Do Longitudinal Data Analysis Using… REDCap, SAS, R, Stata and SPSS
Wednesday, Nov. 30 at 11 a.m.
Longitudinal analysis is a powerful tool to study individual changes over time. This webinar will cover different types of longitudinal analysis (e.g., fixed effects, random effects and mixed effects models), with examples from five different statistical and data management software.
How to Reshape Longitudinal Data Using… REDCap, SAS, R, Stata and SPSS
Wednesday, Oct. 26 at 11 a.m.
Longitudinal data are increasingly common in health research, as they are necessary to study individual changes over time. This webinar will show the steps and best practices to prepare your dataset for a longitudinal analysis using five different statistical and data management software.
How to Do Power Calculations and Sample Size Determinations
Wednesday, Sept. 28 at 11 a.m.
An adequate sample size is crucial for ensuring that statistical tests have the power to detect the relationships outlined in research aims. This session will detail what information is required to enter into sample size calculations and how to perform these calculations in various computing software.
How to Manage Data Using REDCap
Tuesday, Aug. 30 at 10 a.m.
REDCap is a secure, free, software platform designed for robust research data collection. Survey data, case report forms and operational data can be collected and managed all within one database, enhancing the efficiency of any project. The Biostatistics Consultation Core administers REDCap for Arizona State University and will present best practices and guidance on how to design your database to maximize REDCap's functionality. Topics covered will include e-consent, survey distribution, data quality verification, survey scoring and reports/exports to commonly used analysis packages such as SPSS, SAS and R.