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**1 - 5**of**5**### 06-1-0261) and Congressionally

"... Author affiliations appear at the end of this article. Published online ahead of print at www.jco.org on December 9, 2013. ..."

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Author affiliations appear at the end of this article. Published online ahead of print at www.jco.org on December 9, 2013.

### Running head: ORDINAL MEASUREMENT INVARIANCE 1 Testing for measurement invariance with respect to an ordinal variable

"... Portions of this work were presented at 2012 meeting of the Psychometric Society. The ..."

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Portions of this work were presented at 2012 meeting of the Psychometric Society. The

### Kidney and Recipient Weight Incompatibility Reduces Long-Term Graft Survival

"... Long-term function of kidney allografts depends on multiple variables, one of which may be the compatibility in size between the graft and the recipient. Here, we assessed the long-term consequences of the ratio of the weight of the kidney to the weight of the recipient (KwRw ratio) in a multicenter ..."

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Long-term function of kidney allografts depends on multiple variables, one of which may be the compatibility in size between the graft and the recipient. Here, we assessed the long-term consequences of the ratio of the weight of the kidney to the weight of the recipient (KwRw ratio) in a multicenter cohort of 1189 patients who received a transplant between 1995 and 2006. The graft filtration rate increased by a mean of 5.74 ml/min between the third and sixth posttransplantation months among patients with a low KwRw ratio (,2.3 g/kg; P, 0.0001). In this low KwRw ratio group, the graft filtration rate remained stable between 6 months and 7 years but then decreased at a mean rate of 3.17 ml/min per yr (P, 0.0001). In addition, low KwRw ratios conferred greater risk for proteinuria, more antihypertensive drugs, and segmental or global glomeruloscle-rosis. Moreover, a KwRw ratio,2.3 g/kg associated with a 55 % increased risk for transplant failure by 2 years of follow-up. In conclusion, incompatibility between graft and recipient weight is an independent predictor of long-term graft survival, suggesting that avoiding kidney and recipient weight incompatibility may improve

### Multiple Testing for SNP-SNP Interactions

"... Most genetic diseases are complex, i.e. associated to combinations of SNPs rather than indi-vidual SNPs. In the last few years, this topic has often been addressed in terms of SNP-SNP inter-action patterns given as expressions linked by logical operators. Methods for multiple testing in high-dimensi ..."

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Most genetic diseases are complex, i.e. associated to combinations of SNPs rather than indi-vidual SNPs. In the last few years, this topic has often been addressed in terms of SNP-SNP inter-action patterns given as expressions linked by logical operators. Methods for multiple testing in high-dimensional settings can be applied when many SNPs are considered simultaneously. How-ever, another less well-known multiple testing problem arises within a fixed subset of SNPs when the logic expression is chosen optimally. In this article, we propose a general asymptotic approach for deriving the distribution of the maximally selected chi-square statistic in various situations. We show how this result can be used for testing logic expressions- in particular SNP-SNP interaction patterns- while controlling for multiple comparisons. Simulations show that our method provides multiple testing adjustments when the logic expression is chosen such as to maximize the statistic. Its benefit is demonstrated through an application to a real dataset from a large population-based study considering allergy and asthma in KORA. An implementation of our method is available from the Comprehensive R Archive Network (CRAN) as R package ‘SNPmaxsel’.

### Working with Ordinal Predictors∗

, 2009

"... The use of categorical variables in regression modeling is discussed. Some pitfalls in the use of numerically scaled ordinal variables are considered. ∗Prepared for delivery at the annual meeting of the Midwest Political Science Association, Chicago Illinois, April 2-5, 2009. In the day-to-day pract ..."

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The use of categorical variables in regression modeling is discussed. Some pitfalls in the use of numerically scaled ordinal variables are considered. ∗Prepared for delivery at the annual meeting of the Midwest Political Science Association, Chicago Illinois, April 2-5, 2009. In the day-to-day practice of social science, nominal and ordinal variables are the pre-dominant variable types. Survey data sets may contain the occasional numerical variable like “age ” (in years), but that type is grossly outweighed by the categorical indicators. Categor-ical variables are usually subdivided into “nominal ” and “ordinal ” types. The use of ordinal variables is the main focus of this paper. The presentation is not aimed at methodologists, but rather at practitioners who work with these very common data types. The basic idea that differentiates ordinal variables is that, in the eye of the person who uses the data, an observation’s membership in one category can somehow be interpreted as “less ” or “more ” than another observation’s membership in a different category. Ordinal variables may be based on judgment scales, so the ordering is not purely in the mind of