Home > MRCV research

This research has been supported by National Science Foundation grants SES-0418688, SES-0418632, SES-0207212, and SES-0233321 and the National Science and Engineering Council of Canada. If you find the research useful, please let me know in an e-mail to chris@chrisbilder.com! I would be interested in hearing about your use of the work and the MRCV data that you are modeling.

Software

Koziol, N. and Bilder, C. (2013). MRCV: Methods for Analyzing Multiple Response Categorical Variables. R package version 0.1-0. (version 0.4-0 is most current)

Journal articles with supplementary information

Bilder, C. and Loughin, T. (2009). Modeling Multiple-Response Categorical Data from Complex Surveys. The Canadian Journal of Statistics 37(4), 553-570.
- Simulation results and more information on simulation settings
- Files correspond to the NHANES data example: mod_fit_web_final.sas (data analysis program), item_response_table.sas7bdat (data set used in the program), and mult_response_data.sas7bdat (data set used in the program)
Bilder, C. and Loughin, T. (2007). Modeling Association between Two or More Categorical Variables that Allow for Multiple Category Choices. Communications in Statistics: Theory and Methods 36(2), 433-451.
- Additional simulation results
- Non-convergence example for maximum likelihood estimation
- Files corresponding to the marginal modeling approach examples given in Section 4.1 of the paper:
  - control_2MRCV_final.sas - This is the control program for the statistical methods. Use this program to run the programs boot_2MRCV_final.sas, data_gen_resample.sas, and gange_2MRCV.sas.
  - 2_MRCV_example_data.txt - Data set for test waste and waste storage only.
  - boot_2MRCV_final.sas - Fits a generalized loglinear model via the marginal modeling method and use the bootstrap and Rao-Scott approximations to find a p-value for testing the model of interest vs. the saturated model.
  - gange_2mrcv.sas - Finds a vector of multinomial probabilities subject to the constraints of the H_o model.
  - data_gen_resample.sas - Using a set of multinomial probabilities from Gange.sas, this program generates the resamples under the H_o model
- Files corresponding to the marginal modeling approach examples given in Section 4.2 of the paper.
  - control_3MRCV_final.sas - This is the control program for the statistical methods. Use this program to run the programs boot_3MRCV_final.sas, data_gen_resample.sas, and gange_3MRCV.sas.
  - 3_MRCV_example_data.txt - Data set for test waste, waste storage, and sources of veterinary information MRCVs.
  - v_mat_m.csv - File containing the V matrix (see Appendix A) used in the PROC IML code of boot_3MRCV_final.sas and read in control_3MRCV_final.sas (see program comments for more information).
  - boot_3MRCV_final.sas - Fits a generalized loglinear model via the marginal modeling method and use the bootstrap and Rao-Scott approximations to find a p-value for testing the model of interest vs. the saturated model.
  - gange_3MRCV.sas - Finds a vector of multinomial probabilities subject to the constraints of the H_o model.
  - data_gen_resample.sas - Using a set of multinomial probabilities from Gange.sas, this program generates the resamples under the H_o model. This is the same program as listed in the Section 4.1 programs.

Journal articles without supplementary information

Koziol, N. and Bilder, C. (2014). MRCV: A Package for Analyzing Categorical Variables with Multiple Response Options. The R Journal 6, 144-150.
Bilder, C. and Loughin, T. (2004). Testing for Marginal Independence Between Two Categorical Variables with Multiple Responses. Biometrics 60, 241-8.
Bilder, C. and Loughin, T. (2003). Strategies for Modeling Two Categorical Variables with Multiple Category Choices. 2003 Proceedings of the American Statistical Association, Section on Survey Research Methods [CD-ROM], Alexandria, VA: American Statistical Association, 560-567.
Bilder, C. and Loughin, T. (2002). Testing for Conditional Multiple Marginal Independence. Biometrics 58, 200-208.
Bilder, C. and Loughin, T. (2002). Testing for Simultaneous Pairwise Marginal Independence. 2002 Proceedings of the American Statistical Association, Biometrics Section [CD-ROM], Alexandria, VA: American Statistical Association, 254-259.
Bilder, C. and Loughin, T. (2001). On the First-Order Rao-Scott Correction of the Umesh-Loughin-Scherer Statistic. Biometrics 57, 1253-1255.
Bilder, C., Loughin, T., and Nettleton, D. (2000). Multiple Marginal Independence Testing for Pick Any/c Variables. Communications in Statistics: Simulation and Computation 29(4), 1285-1316.

Presentations

Koziol, N. and Bilder, C., "MRCV: a package for analyzing the association between two categorical variables with multiple response options," UseR!, July 11, 2013; Albacete, Spain.
Bilder, C. and Loughin, T. "Modeling multiple-response categorical data from complex surveys," Washington Statistical Society, September 7, 2007; Washington, DC.
Bilder, C. and Loughin, T. "Estimation and testing for association with multiple-response categorical variables from complex surveys," 2007 Joint Statistical Meetings, July 30, 2007; Salt Lake City, UT.
Bilder, C. "Modeling Association Between Two or More Multiple-Response Categorical Variables," Department of Statistics, University of South Carolina, November 4, 2005; Columbia, SC.
Bilder, C. "Modeling Association Between Two or More Multiple-Response Categorical Variables," Department of Statistics, University of Nebraska-Lincoln, September 8, 2004; Lincoln, NE.
Bilder, C. and Loughin, T. "Testing for Marginal Dependence Between Two or More Multiple-Response Categorical Variables," Third Annual Funding Opportunity in Survey and Statistical Research Seminar sponsored by the Federal Committee on Statistical Methodology, June 21, 2004; Washington, DC.
Bilder, C. and Loughin, T. "Modeling Two or More Categorical Variables that Allow for Multiple Category Choices," 2004 IBS ENAR meetings, March 28, 2004; Pittsburgh, PA.
Bilder, C. and Loughin, T. "Strategies for Modeling Two Categorical Variables with Multiple Category Choices," 2003 Joint Statistical Meetings, August 6, 2003; San Francisco, CA.
Bilder, C. "Testing for Marginal Independence between Two or More Multiple-Response Categorical Variables," Department of Statistics, Kansas State University, March 13, 2003; Manhattan, KS.
Bilder, C. and Loughin, T. "Testing for Simultaneous Pairwise Marginal Independence," 2002 Joint Statistical Meetings, August 12, 2002; New York, NY.
Bilder, C. and Loughin, T. "Testing for Marginal Independence Between Two Categorical Variables with Multiple Responses," 2002 IBS ENAR meetings, March 19, 2002; Washington, DC.
Bilder, C. and Loughin, T. "Testing for Conditional Multiple Marginal Independence in the Presence of Pick Any/c Variables," 2001 Joint Statistical Meetings, August 7, 2001; Atlanta, GA.
Bilder, C. and Loughin, T. "Testing for Conditional Multiple Marginal Independence," 2001 IBS ENAR meetings, March 26, 2001; Charlotte, NC.
Bilder, C, Loughin, T., and Nettleton, D. "A Comparison of Multiple Marginal Independence Testing Methods," 2000 Joint Statistical Meetings, August 14, 2000; Indianapolis, IN.