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Transmission Based conditional logistic model for Testing Main and Interaction Effects

Open Journal of Statistics 2021年第5期11卷 713-719页

作者： Caixia Li Peixing Li School of Mathematics Sun Yat-sen University Guangzhou China Guangdong Province Key Laboratory of Computational Science Sun Yat-sen University Guangzhou China

Transmission disequilibrium test (TDT) is a popular family based genetic association method. Under multiplicative assumption, a conditional logistic regression for matched pair, affected offspring with allele transmitted from parents and pseudo-offspring (control) with allele non-transmitted from parents, was built to detect the main effects of genes and gene-covariate interactions. When there exist genotype uncertainties, expectation-maximization (EM) algorithm was adopted to estimate the coefficients. The transmission model was applied to detect the association between M235T polymorphism in AGT gene and essential hypertension (ESH). Most of parents are not available in the 126 families from HongKong Chinese population. The results showed M235T is associated with hypertension and there is interaction between M235T and the case’s sex. The allele T is higher risk for male than female.

关键词： Transmission Disequilibrium Test Gene-Covariate Interaction conditional logistic model Expectation-Maximization Algorithm

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Sample size evaluation for a multiply matched case-control study using the score test from a conditional logistic (discrete Cox PH) regression model

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STATISTICS IN MEDICINE 2008年第14期27卷 2509-2523页

作者： Lachin, John M. George Washington Univ Ctr Biostat Dept Epidemiol & Biostat Rockville MD 20852 USA George Washington Univ Ctr Biostat Dept Stat Rockville MD 20852 USA

The conditional logistic regression model (Biometrics 1982;38:661-672) provides a convenient method for the assessment of qualitative or quantitative covariate effects on risk in a study with matched sets, each containing a possibly different number of cases and controls. The conditional logistic likelihood is identical to the stratified Cox proportional hazards model likelihood, with an adjustment for ties (J. R. Stat. Soc. B 1972;34:187-220). This likelihood also applies to a nested case-control study with multiply matched cases and controls, selected from those at risk at selected event times. Herein the distribution of the score test for the effect of a covariate in the model is used to derive simple equations to describe the power of the test to detect a coefficient theta (log odds ratio or log hazard ratio) or the number of cases (or matched sets) and controls required to provide a desired level of power. Additional expressions are derived for a quantitative covariate as a function of the difference in the assumed mean covariate values among cases and controls and for a qualitative covariate in terms of the difference in the probabilities of exposure for cases and controls. Examples are presented for a nested case-control study and a multiply matched case-control study. Copyright (C) 2007 John Wiley & Sons, Ltd.

关键词： sample size power conditional logistic model Cox proportional hazards model multiple matching case-control study nested case-control study

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Testing for ordered group effects in binary and continuous outcomes

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BIOMETRICAL JOURNAL 2007年第4期49卷 585-598页

作者： Farrell, Patrick J. Park, Chul Gyu Carleton Univ Sch Math & Stat Ottawa ON K1S 5B6 Canada

A likelihood ratio test is proposed for the detection of an ordered group effect on bivariate responses where one response is binary and the other is continuous. The procedure is based on a conditional logistic model for the binary response given the continuous outcome. We also develop a likelihood ratio test for simultaneously determining the goodness of fit of the ordering assumption on both responses. Our approach is motivated by a particular toxicity study application involving laboratory animals that focused on the effect of a food color additive on the development of reticuloendothelial (RE) tumors. A brief discussion on extensions to the methodology introduced here is also given, along with a comparison of the approach with a marginal strategy where the presence of an ordered group effect is assessed independently for each of the two responses.

关键词： bivariate discrete and continuous outcomes conditional logistic model joint analysis likelihood ratio test ordered hypothesis

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Evaluating the welfare effects of improved wastewater treatment using a discrete choice experiment

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2013年 123卷 49-57页

作者： Ndunda, Ezekiel N. Mungatana, Eric D. Univ Pretoria Fac Nat & Agr Sci CEEPA Dept Agr Econ Extens & Rural Dev ZA-0002 Pretoria South Africa

This paper employs the discrete choice experiment method to estimate the benefits of improved wastewater treatment programs to mitigate the impacts of water pollution in Nairobi, Kenya. Urban and pen-urban farmers who use wastewater for irrigation from Motoine to Ngong River in Nairobi were randomly selected for the study. A random parameter logit model was used to estimate the individual level willingness to pay for the wastewater treatment before reuse in irrigation. The results show that urban and pen-urban farmers are willing to pay significant monthly municipality taxes for treatment of wastewater. We find that the quality of treated wastewater, the quantity of treated wastewater and the riverine ecosystem restoration are significant factors of preference over alternative policy designs in reduction of water pollution. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： conditional logistic model Constructed wetland technology Discrete choice experiment Random parameter logit model Wastewater treatment Riverine ecosystem restoration

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A new algorithm for solving binary discrimination in conditional logistic regression, with two choices of strata

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2005年第1期49卷 85-97页

作者： Fu, CY Hung, JH Liu, SH Chien, YL Natl Yang Ming Univ Inst Publ Hlth Taipei 112 Taiwan Natl Yang Ming Univ Sch Med Taipei 112 Taiwan Vet Gen Hosp Dept Obstet & Gynecol Taipei Taiwan

When conditional logistic regression is based on the exact conditional distribution for inference, the intercept is eliminated. This becomes a problem when the predicted probability is a key issue for binary discrimination. This report details a new algorithm for risk score instead of predicted probability for stratified data in binary discrimination. From the statistical point of view, data partition will reduce the variation of data. Comparing the data-inherent strata and strata generated from the Classification and Regression Tree (CART), the strata generated from CART had greater variation reduction than did the data-inherent strata. Finally, the conditional logistic regression algorithm, used for discrimination when modeling fetal biometric data, resulted in cost savings and computer time savings benefits. (C) 2004 Elsevier B.V. All rights reserved.

关键词： conditional logistic model binary discrimination strata risk score ROC CART fetal biometric data

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Development of crash modification factors of horizontal curve design features for single-motorcycle crashes on rural two-lane highways: A matched case-control study

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ACCIDENT ANALYSIS AND PREVENTION 2019年 123卷 51-59页

作者： Xin, Chunfu Wang, Zhenyu Lee, Chanyoung Lin, Pei-Sung Chen, Tao Guo, Rui Lu, Qing Univ S Florida Dept Civil & Environm Engn 4202 E Fowler AveENB118 Tampa FL 33620 USA Univ S Florida Ctr Urban Transportat Res 4202 E Fowler AveCUT100 Tampa FL 33620 USA Chang An Univ Key Lab Automot Transportat Safety Tech Minist Transport 2nd Ring Rd South East Sect Xian 710064 Shanxi Peoples R China Texas Tech Univ Civil Environm & Construct Engn 2500 Broadway Lubbock TX 79409 USA

Single-motorcycle crashes are overrepresented on horizontally curved segments of rural, two-lane, undivided (RTU) highways. However, the relationship between single-motorcycle crash risk and the design features of horizontal curves on RTU highways is not well-studied in existing literature. This study aims to quantify the effect of horizontal curve type and radius on the risk of single-motorcycle crashes with a matched case-control study that can address the issues of the low sample mean, aggregation bias, and uncontrolled confounders existing in the traditional cross-sectional study. In the matched case-control study, three matching factors-year, annual average daily traffic (AADT), and segment length-were selected to match controls (RTU segments without crash records) with cases (RTU segments with crash records). A total of 1601 cases and 16,010 matched controls over 11 years (2005-2015) were identified as matched-strata. A conditional logistic model was fitted on the matched-strata data to estimate the crash modification factors (CMFs) of horizontal curve design features for single-motorcycle crashes. The modeling results highlighted the interaction effects between curve type and radius on the risk of single-motorcycle crashes. Sharp (radius <= 1500 ft) non-reverse curves were identified as the riskiest curve design for motorcyclists, followed by sharp reverse curves and moderate (1500 ft < radius <= 3000 ft) reverse curves. The study also revealed that motorcyclists might take safety-compensation behaviors on sharp curves, narrow shoulders, and poor pavement conditions. Engineering and education countermeasures are suggested for comprehending curve presence and associated risk level, reducing curve entry speed, and improving safety awareness. Finally, the limitations of the study and possible solutions are discussed.

关键词： Motorcycle crash Low mean problem Aggregation-bias issue Matched case-control study conditional logistic model Crash modification factor

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On the impact of residential history in the spatial analysis of diseases with a long latency period: A study of mesothelioma in Belgium

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STATISTICS IN MEDICINE 2020年第26期39卷 3840-3866页

作者： Petrof, Oana Neyens, Thomas Nuyts, Valerie Nackaerts, Kristiaan Nemery, Benoit Faes, Christel Hasselt Univ Data Sci Inst BioStat 1 Diepenbeek Belgium Katholieke Univ Leuven Leuven Biostat & Stat Bioinformat Ctr L BioStat Dept Publ Hlth & Primary Care Leuven Belgium Univ Leuven Ctr Environm & Hlth Dept Publ Hlth & Primary Care Leuven Belgium Katholieke Univ Leuven Univ Hosp Leuven Dept Pneumol Leuven Belgium

Mesothelioma is a rare cancer caused by exposure to asbestos. Belgium has a known long history of asbestos production, resulting in one of the highest mesothelioma mortality rates worldwide. While the production of asbestos has stopped completely, the long latency period of mesothelioma, which can fluctuate between 20 and 40 years after exposure, causes incidences still to be frequent. Mesothelioma's long incubation time affects our assessment of its geographical distribution as well. Since patients' residential locations are likely to change a number of times throughout their lives, the location where the patients develop the disease is often far from the location where they were exposed to asbestos. Using the residential history of patients, we propose the use of a convolution multiple membership model (MMM), which includes both a spatial conditional autoregressive and an unstructured random effect. Pancreatic cancer patients are used as a control population, reflecting the population at risk for mesothelioma. Results show the impact of the residential mobility on the geographical risk estimation, as well as the importance of acknowledging the latency period of a disease. A simulation study was conducted to investigate the properties of the convolution MMM. The robustness of the results for the convolution MMM is assessed via a sensitivity analysis.

关键词： conditional logistic model convolution model latency period multiple membership model residential history

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Linkage analysis of alcoholism-related electrophysiological phenotypes: genome scans with microsatellites compared to single-nucleotide polymorphisms

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BMC GENETICS 2005年第s1期6卷 S156-S156页

作者： Bautista, JF Quade, SRE Parrado, AR Goddard, KAB Case Western Reserve Univ Dept Epidemiol & Biostat Cleveland OH 44106 USA Cleveland Clin Fdn Dept Neurol Cleveland OH 44195 USA

P300 amplitude is an electrophysiological quantitative trait that is correlated with both alcoholism and smoking status. Using the Collaborative Study on the Genetics of Alcoholism data, we performed model- free linkage analysis to investigate the relationship between alcoholism, P300 amplitude, and habitual smoking. We also analyzed the effect of parent-of-origin on alcoholism, and utilized both microsatellites ( MS) markers and single- nucleotide polymorphisms ( SNPs). We found significant evidence of linkage for alcoholism to chromosome 10;inclusion of P300 amplitude as a covariate provided additional evidence of linkage to chromosome 12. This same region on chromosome 12 showed some evidence for a parent-of-origin effect. We found evidence of linkage for the P300 phenotype to chromosome 7 in non-smokers, and to chromosome 17 in alcoholics. The effects of alcoholism and habitual smoking on P300 amplitude appear to have separate genetic determinants. Overall, there were few differences between MS and SNP genome scans. The use of covariates and parent-of-origin effects allowed detection of linkage not seen otherwise.

关键词： Linkage Analysis P300 Amplitude Habitual Smoking conditional logistic model Recurrence Risk Ratio

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Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors

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GENE 2018年 659卷 118-122页

作者： Naseri, Parisa Khodakarim, Soheila Guity, Kamran Daneshpour, Maryam S. Shahid Beheshti Univ Med Sci Sch Paramed Sci Dept Biostat Tehran Iran Shahid Beheshti Univ Med Sci Sch Paramed Sci Sch Publ Hlth Dept Epidemiol Tehran Iran Shahid Beheshti Univ Med Sci Res Inst Endocrine Sci Cellular & Mol Endocrine Res Ctr POB 19195-4763 Tehran Iran

Background: Mechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). Materials and methods: The design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of EIDL_C according to ATP III criteria. In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. Results: The results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. Conclusions: In summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates.

关键词： HDL_C Mets Aggregation analysis Linkage analysis conditional logistic model

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Analysis of alcohol dependence phenotype in the COGA families using covariates to detect linkage

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BMC GENETICS 2005年第Sup1期6卷 S143-S143页

作者： Reck, BH Mukhopadhyay, N Tsai, HJ Weeks, DE Univ Pittsburgh Grad Sch Publ Hlth Dept Human Genet Pittsburgh PA 15261 USA Univ Calif San Francisco San Francisco CA 94143 USA Univ Pittsburgh Grad Sch Publ Hlth Dept Biostat Pittsburgh PA 15261 USA San Francisco Gen Hosp Lung Biol Ctr San Francisco CA 94110 USA

Linkage analysis methods that incorporate etiological heterogeneity of complex diseases are likely to demonstrate greater power than traditional linkage analysis methods. Several such methods use covariates to discriminate between linked and unlinked pedigrees with respect to a certain disease locus. Here we apply several such methods including two mixture models, ordered subset analysis, and a conditional logistic model to genome scan data on the DSM-IV alcohol dependence phenotype on the Collaborative Studies on Genetics of Alcoholism families, and compare the results to traditional nonparametric linkage analysis. In general, there was little agreement among the various covariate-based linkage statistics. Linkage signals with empirical p-values less than 0.001 were detected on chromosomes 3, 4, 7, 10, and 12, with the highest peak occurring at the GABRB1 gene using the ecb21 covariate.

关键词： DRD2 Gene Empirical Null Distribution Nonparametric Linkage Analysis Order Subset Analysis conditional logistic model

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