## Research Topics- statistical models
- biometry
- statistical data interpretation
- nonparametric statistics
- therapeutics
- comorbidity
- retinitis pigmentosa
- exudates and transudates
- ophthalmology
- pruritus
- beta carotene
- retinal detachment
- matched pair analysis
- incidence
- eye diseases
- diabetic retinopathy
- sample size
- body size
- thromboembolism
- vitamin e
- cataract
- intraocular pressure
- physicians
- aspirin
- likelihood functions
- nutritional status
- venous thrombosis
- roc curve
- area under curve
- alcohol drinking
| ## STATISTICAL METHODS FOR OPHTHALMOLOGIC AND CLUSTER DATA## SummaryPrincipal Investigator: B Rosner Affiliation: Harvard University Country: USA Abstract: DESCRIPTION: (Applicant's Abstract) The analysis of ophthalmological data pose unique challenges for the data analyst because the fundamental unit of analysis is not well defined. If the eye is used as the unit of analysis, then one must account for the correlation between fellow eyes in performing the analysis; otherwise one will underestimate p- values and widths of confidence intervals. There has been much interest in he past 15 years in the development of techniques for addressing this issue including GEE methods (Liang and Zeger, 1986) and generalized linear models (Rosner, 1984). Most of these methods are concerned with parametric statistical models such as linear or logistic regression. One gap in the literature that we intend to fill in this proposal is the incorporation of clustering effects for standard nonparametric tests. Many types of ophthalmologic data are not normally distributed (e.g. Humphrey visual field data), and require nonparametric methods for their analysis. If one wishes to use the eye as the unit of analysis, then it is important to incorporate clustering effects into these methods that take the correlation between fellow eyes into account. Many ophthalmologists prefer to use the person as the unit of analysis (e.g. using visual function in the better eye) rather than the eye. However, Olkin and Viana (1995) showed that the distribution of visual function in the better eye as a function of a person-specific covariate (e.g. age) is not normally distributed, and propose special methods for this type of analysis. We propose to extend this work to the case of eye specific covariates and the case of several covariates in the same model. Another issue is that some ophthalmic conditions (e.g. cataract) have subclassifications with possibly different etiologies (e.g. nuclear, cortical, PSC cataract). However, the important public health question is: what is the overall probability of any type of cataract as a function of risk factors (e.g., antioxidant use). We intent to generalize the standard logistic model, to be compound logistic model which accounts for the possibly differential risk factor profiles. Furthermore, there has been much work on censored survival data where the failure times occur only at specific visits. We intend to incorporate clustering effects in interval censored data. A final goal of our proposal is to perform an analysis of the natural course of retinitis pigmentosa over a 12 year period. This will allow estimation of the rates of decline of the ERG and visual field over a long period of time as well as provide estimates for an individual patient of the number of years of useful vision they can expect to have. Funding Period: 1998-08-01 - 2002-07-31 more information: NIH RePORT ## Top Publications- Comparison of risk factors for the competing risks of coronary heart disease, stroke, and venous thromboembolismRobert J Glynn
Division of Preventive Medicine and the Channing Laboratory, Brigham and Women s Hospital, Harvard Medical School, Boston, MA 02215, USA*Am J Epidemiol*162:975-82. 2005 - Statistical inference for correlated data in ophthalmologic studiesMan Lai Tang
Department of Mathematics, Hong Kong Baptist University, Kowloon, Hong Kong*Stat Med*25:2771-83. 2006 - The Wilcoxon signed rank test for paired comparisons of clustered dataBernard Rosner
Channing Laboratory, Harvard Medical School, Boston, Massachusetts 02115, USA*Biometrics*62:185-92. 2006 - Extension of the rank sum test for clustered data: two-group comparisons with group membership defined at the subunit levelBernard Rosner
Channing Laboratory, Harvard Medical School, Boston, Massachusetts 02115, USA*Biometrics*62:1251-9. 2006 - A nonparametric test for observational non-normally distributed ophthalmic data with eye-specific exposures and outcomesBernard Rosner
Channing Laboratory, Harvard Medical School, Boston, Massachusetts 02115, USA*Ophthalmic Epidemiol*14:243-50. 2007 - Power and sample size estimation for the Wilcoxon rank sum test with application to comparisons of C statistics from alternative prediction modelsB Rosner
Channing Laboratory, Harvard Medical School, Boston, Massachusetts 02115, USA*Biometrics*65:188-97. 2009 - Evaluation of risk factors for cataract types in a competing risks frameworkRobert J Glynn
Division of Preventive Medicine, Brigham and Women s Hospital, Harvard Medical School, Boston, Massachusetts 02215, USA*Ophthalmic Epidemiol*16:98-106. 2009
| ## Scientific Experts |

## Detail Information

### Publications

- Comparison of risk factors for the competing risks of coronary heart disease, stroke, and venous thromboembolismRobert J Glynn

Division of Preventive Medicine and the Channing Laboratory, Brigham and Women s Hospital, Harvard Medical School, Boston, MA 02215, USA*Am J Epidemiol*162:975-82. 2005..CHD and stroke have broadly comparable risk factor profiles that differ widely from the profile for VTE... - Statistical inference for correlated data in ophthalmologic studiesMan Lai Tang

Department of Mathematics, Hong Kong Baptist University, Kowloon, Hong Kong*Stat Med*25:2771-83. 2006..8). On the other hand, the approximate unconditional procedures usually yield empirical type I error rates close to the pre-chosen nominal level. We illustrate our methodologies with a data set from a retinal detachment study... - The Wilcoxon signed rank test for paired comparisons of clustered dataBernard Rosner

Channing Laboratory, Harvard Medical School, Boston, Massachusetts 02115, USA*Biometrics*62:185-92. 2006.... - Extension of the rank sum test for clustered data: two-group comparisons with group membership defined at the subunit levelBernard Rosner

Channing Laboratory, Harvard Medical School, Boston, Massachusetts 02115, USA*Biometrics*62:1251-9. 2006..We also present comparisons between the clustered Wilcoxon test and each of the signed rank tests and mixed model approaches and show dramatic differences in power in favor of the clustered Wilcoxon test for some designs... - A nonparametric test for observational non-normally distributed ophthalmic data with eye-specific exposures and outcomesBernard Rosner

Channing Laboratory, Harvard Medical School, Boston, Massachusetts 02115, USA*Ophthalmic Epidemiol*14:243-50. 2007.... - Power and sample size estimation for the Wilcoxon rank sum test with application to comparisons of C statistics from alternative prediction modelsB Rosner

Channing Laboratory, Harvard Medical School, Boston, Massachusetts 02115, USA*Biometrics*65:188-97. 2009..These results are based on SAS-callable functions to evaluate the bivariate normal integral and are thus easily implemented with standard software... - Evaluation of risk factors for cataract types in a competing risks frameworkRobert J Glynn

Division of Preventive Medicine, Brigham and Women s Hospital, Harvard Medical School, Boston, Massachusetts 02215, USA*Ophthalmic Epidemiol*16:98-106. 2009..One can compare the impact of risk factors on different types of cataract with methods of competing risk survival analysis that account for tied events...