caa a22 4500 606196455 CHVBK 20210128100924.0 cr unu---uuuuu 210128e20150901xx s 000 0 eng 10.1007/s10260-014-0285-4 doi (NATIONALLICENCE)springer-10.1007/s10260-014-0285-4 Analysis of an outcome-dependent enriched sample: hypothesis tests [Elektronische Daten] [Christopher Vahl, Qing Kang] An outcome-dependent sample is generated by a stratified survey design where the stratification depends on the outcome. It is also known as a case-control sample in epidemiological studies and a choice-based sample in econometrical studies. An outcome-dependent enriched sample (ODE) results from combining an outcome-dependent sample with an independently collected random sample. Consider the situation where the conditional probability of a categorical outcome given its covariates follows an explicit model with an unknown parameter whereas the marginal probability of the outcome and its covariates are left unspecified. Profile-likelihood (PL) and weighted-likelihood (WL) methods have been employed to estimate the model parameter from an ODE sample. This article develops the PL- and WL-based families of tests on the model parameter from an ODE sample. Asymptotic properties of their test statistics are derived. The PL likelihood-ratio, Wald and score tests are shown to obey classical inference, i.e. their test statistics are asymptotically equivalent and Chi-squared distributed. In contrast, the WL likelihood-ratio statistic asymptotically has a weighted Chi-squared distribution and is not equivalent to the WL Wald and score statistics. Our theoretical derivation and simulation show that tests based on these new statistics carry nominal type I error and good power. Advantages of ODE sampling together with the implementation of the PL and WL methods are demonstrated in an illustrative example. Springer-Verlag Berlin Heidelberg, 2014 Likelihood-ratio test nationallicence Outcome-dependent sample nationallicence Profile likelihood nationallicence Score test nationallicence Wald test nationallicence Weighted likelihood nationallicence Vahl Christopher Department of Statistics, Kansas State University, 101 Dickens Hall, 66506, Manhattan, KS, USA aut Kang Qing 117 Firethorn Lane, 66503, Manhattan, KS, USA aut Statistical Methods & Applications Springer Berlin Heidelberg 24/3(2015-09-01), 387-409 1618-2510 24:3<387 2015 24 10260 https://doi.org/10.1007/s10260-014-0285-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10260-014-0285-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Vahl Christopher Department of Statistics, Kansas State University, 101 Dickens Hall, 66506, Manhattan, KS, USA aut NATIONALLICENCE 700 1- Kang Qing 117 Firethorn Lane, 66503, Manhattan, KS, USA aut NATIONALLICENCE 773 0- Statistical Methods & Applications Springer Berlin Heidelberg 24/3(2015-09-01), 387-409 1618-2510 24:3<387 2015 24 10260