Difference between revisions of "SOCR Simulated HELP Data Activity"

Revision as of 17:40, 12 September 2014

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".

R examples

These simulated HELP data can be used to demonstrate (using SOCR and R)a number of different statistical, modeling, inferential and data analytic techniques.

Data I/O, summaries, visualization

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

SOCR Home page: http://www.SOCR.ucla.edu

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@@ Line 4: / Line 4: @@
 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==
+==R examples==
-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_Simulated_HELP_Data_Activity|SOCR HELP Activity]] demonstrates exemplary use of these data using R.
+These simulated HELP data can be used to demonstrate (using [[SOCR]] and [http://www.r-project.org/ R])a number of different statistical, modeling, inferential and data analytic techniques.
-* Data I/O, summaries, visualizaiton
-* Derived variables and data manipulation
-* Sorting and subsetting
-* [[SMHS_EDA|Exploratory data analysis]]
-* [[SOCR_EduMaterials_ChartsActivities|Graphing and plotting of data (scatterplot, bubble chart, multiple plots, dotplot, etc.)]]
-* [[SMHS_SLR|Bivariate relationship]]
-* [[AP_Statistics_Curriculum_2007_Contingency_Indep|Contingency tables]]
-* [[SMHS_HypothesisTesting|Two-sample tests]]
-* [[SMHS_SurvivalAnalysis|Survival analysis (Kaplan–Meier plot)]]
-* [[SOCR_EduMaterials_Activities_ScatterChart|Scatterplot with smooth fit]]
-* [[SMHS_SLR|Regression with prediction intervals]]
-* Linear regression with interaction
-* Regression diagnostics
-* Fitting stratified regression models
-* [[SMHS_ANOVA|Two-way analysis of variance (ANOVA)]]
-* [[SMHS_CorrectionMultipleTesting|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
-* [[SOCR_EduMaterials_Activities_PowerTransformFamily_Graphs|Data transformations]]
-* General linear model for correlated data
-* Random effects model
-* [[SMHS_GEE|Generalized estimating equations (GEE) model]]
-* Generalized linear mixed model
-* Proportional hazards regression model
-* Bayesian Poisson regression
-* [[SMHS_Cronbachs|Cronbach’s $\alpha$]]
-* [[SMHS_PCA_ICA_FA|Factor analysis]]
-* Recursive partitioning
-* Linear discriminant analysis
-* [[SMHS_HLM|Hierarchical clustering]]
-* [[SMHS_ROC|ROC curve]]
-* [[SMHS#Chapter_IV:_Special_Topics|Multiple imputation]]
-* Propensity score modeling
+===Data I/O, summaries, visualization===
+===Derived variables and data manipulation===
+===Sorting and subsetting===
+===[[SMHS_EDA|Exploratory data analysis]]===
+===[[SOCR_EduMaterials_ChartsActivities|Graphing and plotting of data (scatterplot, bubble chart, multiple plots, dotplot, etc.)]]===
+===[[SMHS_SLR|Bivariate relationship]]===
+===[[AP_Statistics_Curriculum_2007_Contingency_Indep|Contingency tables]]===
+===[[SMHS_HypothesisTesting|Two-sample tests]]===
+===[[SMHS_SurvivalAnalysis|Survival analysis (Kaplan–Meier plot)]]===
+===[[SOCR_EduMaterials_Activities_ScatterChart|Scatterplot with smooth fit]]===
+===[[SMHS_SLR|Regression with prediction intervals]]===
+===Linear regression with interaction===
+===Regression diagnostics===
+===Fitting stratified regression models===
+===[[SMHS_ANOVA|Two-way analysis of variance (ANOVA)]]===
+===[[SMHS_CorrectionMultipleTesting|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===
+===[[SOCR_EduMaterials_Activities_PowerTransformFamily_Graphs|Data transformations]]===
+===General linear model for correlated data===
+===Random effects model===
+===[[SMHS_GEE|Generalized estimating equations (GEE) model]]===
+===Generalized linear mixed model===
+===Proportional hazards regression model===
+===Bayesian Poisson regression===
+===[[SMHS_Cronbachs|Cronbach’s $\alpha$]]===
+===[[SMHS_PCA_ICA_FA|Factor analysis]]===
+===Recursive partitioning===
+===Linear discriminant analysis===
+===[[SMHS_HLM|Hierarchical clustering]]===
+===[[SMHS_ROC|ROC curve]]===
+===[[SMHS#Chapter_IV:_Special_Topics|Multiple imputation]]===
+===Propensity score modeling===