You are here: Vanderbilt Biostatistics Wiki>Main Web>Seminars>WednesdaySeminarSeries>FrankHarrellAugust272014 (21 Aug 2014, AshleeBartley)EditAttach

A hindrance in analyzing continuous Y is that there may be thousands of unique Y values, necessitating inclusion of thousands of intercepts in the model. Fortunately, the portion of the information matrix corresponding to the intercept parameters is tri-band diagonal, so inverting the matrix is almost instant once the sparse nature of the matrix is capitalized upon. The new orm function in the R rms package uses this approach, just as SAS JMP did more than 20 years ago (Sall, 1991).

This talk includes a case study in development of a screening model to predict current HbA1c using NHANES data, and covers model diagnostics and some statistical and computing issues. The case study demonstrates how ordinal models allow the analyst to easily obtain an array of estimates from quantiles to exceedance probabilities to moments. Ordinal regression is not only a possible replacement for linear models but is more efficient at estimating quantiles than quantile regression in some cases, and get around quantile regression's assumption that Y is completely continuous.

The talk also includes a diversion about evils of dichotomization in medical diagnosis.

The full case study may be found at

Edit | Attach | Print version | History: r1 | Backlinks | View wiki text | Edit wiki text | More topic actions

Topic revision: r1 - 21 Aug 2014, AshleeBartley

Copyright © 2013-2017 by the contributing authors. All material on this collaboration platform is the property of the contributing authors.

Ideas, requests, problems regarding Vanderbilt Biostatistics Wiki? Send feedback

Ideas, requests, problems regarding Vanderbilt Biostatistics Wiki? Send feedback