R Programs
R ProgramsSome Helpful Resources
- R for Beginners, by Emmanuel Paradis (58 pages)
- New! R Package for Visualizing Categorical Data
- The vcd Package (documentation)
- Note: If you your current R version does NOT have the new {vcd} package, you can download it from the package page above.
- S-PLUS (and R) Manual to Accompany Agresti’s Categorical Data Analysis (2002) 2nd edition (1.6 MB, 265 pages)
- Alan Agresti's Website for CATEGORICAL DATA ANALYSIS, 2nd edition.
- Penn State students can also access R Software video tutorials by logging into Lynda.psu.edu with their Penn State userid and password.
| The Topic / Procedure | Page |
R code - text data file
|
| Different chi-squared distributions | chisqdistributions.R | |
| Binomial Likelihood | ||
| Simple Binomial Calculations in R | 2.3.2 | |
| Basic Poisson Calculations in R | 2.3.1 | |
|
Goodness-of-Fit Test: Cell Probabilities Functions of Unknown Parameters |
2.7 | |
| Creates a table of one-way frequencies for observations of a die and then finds calculates a one-way chi-square test | 2.5 | |
| Binomial test of proportions | 2.3.2 | |
| Poisson sampling and goodness of fit with one-way table Datafile: soccer2002.txt |
2.3.1 | |
| Goodness of fit with X2 with G2 | 2.5 | |
| Test of independence, and measures of associations for a 2 × 2 table | 3.1.5 | |
| Test of independence, and measures of associations for an I × J table | ||
| Test of independence, and measures of associations for an I × J table; simple data visualization | 3.2.3 | |
| Enters tea tasting data and performs one-sided and two-side Fisher's exact test for count data. | 3.3 | |
| Enters the voters data and performs McNemar's test for 2 × 2 tables | 4.2.3 | |
| Cohen's kappa | 4.2.5 | |
| Takes the marginal counts specified for by each parameter and using these to estitmate the contents of a specific cell. This is used to test for mutual independence. Also for other independence models. | 5.3 | |
| Test for various independence models in a 3-way table | 5.4.1 | |
|
Tests for various independence models in a 3-way table (Datafile: berkeley.txt) Loglinear models Simpson's paradox |
5.4.6 | |
| Logistic Regression for 2-way tables | 6.2.2 | |
| Logistic Regression for 3-way tables | 6.3.1 | |
| Logistic Regression with continuous covariates | 7.1.1 | |
| ROC analysis, plot the ROC curve and a Hosmer-Lemeshow test | 7.1.1 | ROCandHL.R |
|
CASE STUDY: The Water Level Study Water Level Study 2 (.doc) WaterStudyLogisticRegression.pdf Datafile: water_level.txt |
7.1.1 | |
| Logistic regression | 7.2.1 | |
| Baseline-category logit model | 8.2.2 | |
| Proportional-odds cumulative logit model | 8.4.1 | cheese.dat cheese.r |
| Proportional-odds cumulative logit model Datafile: abortion.txt |
8.4.2 | abortion.r |
| Poisson Regression | 9.2 | |
| Poisson Regression with rates Datafile: creditcard.txt |
9.3 | |
| CASE STUDY: The Ice Cream Study at Penn State | ||
|
CASE STUDY: Stress and Smoking Datafile: stress.txt |
||
| Loglinear models for 2 × 2 tables | 10.1.2 | VitaminCLoglin.R VitaminCLoglin.out |
| Loglinear model of independence for two-way table | 10.1.3 | vote.R |
| Loglinear models 3-way tables | 10.2 | berkeleyLoglin.R |
|
Loglinear models; model assessment and selection |
10.2.9 | collar.out |
| Sparse data: Sampling & Structural Zeros | 11.1.1 | ZerosEx.R |
| Sparse data: Incomplete table analysis | 11.1.3 | health.R health3.R |
| Ordinal data: Linear by linear association model | 11.2.1 | HeartDiseaseLoglin.R |
| Dependent data: loglinear models | 11.3.2 | movies.R |
| Dependent data: quasi-independence loglinear model | 11.3.5 | monkey.R |