Test of Association Between Two Ordinal Variables While Adjusting for Covariates

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Test of Association Between Two Ordinal Variables While Adjusting for Covariates.

We propose a new set of test statistics to examine the association between two ordinal categorical variables X and Y after adjusting for continuous and/or categorical covariates Z. Our approach first fits multinomial (e.g., proportional odds) models of X and Y, separately, on Z. For each subject, we then compute the conditional distributions of X and Y given Z. If there is no relationship betwe...

متن کامل

Residual-based Test of Conditional Association between Continuous and Ordinal Variables with Application to Genome-wide Association Studies

The discovery of genes linked with a large array of diseases has been accelerated by genome-wide association studies (GWAS), in which genetic variants in different individuals are examined for relationship with a specified phenotype. Most GWAS analyses require modeling the association between single nucleotide polymorphisms (SNPs) and the outcome of interest as additive, dominant, or recessive....

متن کامل

Adjusting for Dependent Censoring Using Many Covariates

Right-censored data are common in many epidemiological studies. One main goal is to estimate the survival function of lifetime. However, if this right-censoring is dependent and is explained by high-dimensional covariates, estimating the survival function of lifetime by using either semiparametric models or nonparametric methods can be problematic. In this paper, we condense these high-dimensio...

متن کامل

A Remark on Adjusting for Covariates

A formula is given to determine the impact of adjusting for covariates on the accuracy of estimates in a multiple regression model.

متن کامل

Adjusting the generalized ROC curve for covariates.

Receiver operating characteristic (ROC) curves and in particular the area under the curve (AUC), are widely used to examine the effectiveness of diagnostic markers. Diagnostic markers and their corresponding ROC curves can be strongly influenced by covariate variables. When several diagnostic markers are available, they can be combined by a best linear combination such that the area under the R...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of the American Statistical Association

سال: 2010

ISSN: 0162-1459,1537-274X

DOI: 10.1198/jasa.2010.tm09386