Difference between revisions of "SOCR Simulated HELP Data Activity"
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==[[SOCR_Simulated_HELP_Data|SOCR Simulated HELP Data]]== | ==[[SOCR_Simulated_HELP_Data|SOCR Simulated HELP Data]]== | ||
| − | See the [[SOCR_Simulated_HELP_Data|SOCR Simulated HELP Data]] first. These data can be copy-pasted using the mouse from the HTML table into a plain text file "help_data.csv". | + | See the [[SOCR_Simulated_HELP_Data|SOCR Simulated HELP Data]] first. These data can be copy-pasted using the mouse from the HTML table into a plain text file [http://socr.umich.edu/data/SOCR_HELP_SIm_Data_2014.csv "help_data.csv"]. |
==Classroom use of this data set== | ==Classroom use of this data set== | ||
Revision as of 17:34, 12 September 2014
Contents
SOCR Simulated HELP Data - SOCR Activity: Simulated Health Evaluation and Linkage to Primary (HELP) Care Dataset
SOCR Simulated HELP Data
See the SOCR Simulated HELP Data first. These data can be copy-pasted using the mouse from the HTML table into a plain text file "help_data.csv".
Classroom use of this data set
The simulated HELP data can be used to demonstrate a number of different statistical, modeling, inferential and data analytic techniques, see list below. The following SOCR HELP Activity demonstrates exemplary use of these data using R.
- Data I/O, summaries, visualizaiton
- Derived variables and data manipulation
- Sorting and subsetting
- Exploratory data analysis
- Graphing and plotting of data (scatterplot, bubble chart, multiple plots, dotplot, etc.)
- Bivariate relationship
- Contingency tables
- Two-sample tests
- Survival analysis (Kaplan–Meier plot)
- Scatterplot with smooth fit
- Regression with prediction intervals
- Linear regression with interaction
- Regression diagnostics
- Fitting stratified regression models
- Two-way analysis of variance (ANOVA)
- Multiple comparisons
- Contrasts
- Logistic regression
- Poisson regression
- Zero-inflated Poisson regression
- Negative binomial regression
- Lasso model selection
- Quantile regression
- Ordinal logit regression
- Multinomial logit regression
- Generalized additive model
- Data transformations
- General linear model for correlated data
- Random effects model
- Generalized estimating equations (GEE) model
- Generalized linear mixed model
- Proportional hazards regression model
- Bayesian Poisson regression
- Cronbach’s $\alpha$
- Factor analysis
- Recursive partitioning
- Linear discriminant analysis
- Hierarchical clustering
- ROC curve
- Multiple imputation
- Propensity score modeling
References
- Evaluation and Linkage to Primary (HELP) Care study
- Data formats: help.csv and help.Rdata
- Study and Data specifications
- SAS and R Data Management, Statistical Analysis, and Graphics, Kleinman / Horton, 2009
- SOCR Home page: http://www.SOCR.ucla.edu
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