Abstract:
:The analysis of fecundity data is challenging and requires consideration of both highly timed and interrelated biologic processes in the context of essential behaviors such as sexual intercourse during the fertile window. Understanding human fecundity is further complicated by presence of a sterile population, i.e. couples unable to achieve pregnancy. Modeling techniques conducted to date have largely relied upon discrete time-to-pregnancy survival or day-specific probability models to estimate the determinants of time-to-pregnancy or acute effects, respectively. We developed a class of semi-parametric grouped transformation cure models that capture day-level variates purported to affect the cycle-level hazards of conception and, possibly, sterility. Our model's performance is assessed using simulation and longitudinal data from one of the few prospective cohort studies with preconception enrollment of women followed for 12 menstrual cycles at risk for pregnancy.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
McLain AC,Sundaram R,Buck Louis GMdoi
10.1177/0962280212438646subject
Has Abstractpub_date
2016-02-01 00:00:00pages
22-36issue
1eissn
0962-2802issn
1477-0334pii
0962280212438646journal_volume
25pub_type
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journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280213497432
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abstract::Many statistical studies report p-values for inferential purposes. In several scenarios, the stochastic aspect of p-values is neglected, which may contribute to drawing wrong conclusions in real data experiments. The stochastic nature of p-values makes their use to examine the performance of given testing procedures o...
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journal_title:Statistical methods in medical research
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doi:10.1177/096228020101000604
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abstract::Statistical methods for spatial health data to identify the significant covariates associated with the health outcomes are of critical importance. Most studies have developed variable selection approaches in which the covariates included appear within the spatial domain and their effects are fixed across space. Howeve...
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doi:10.1177/0962280215627184
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abstract::Covariate-adaptive designs are widely used to balance covariates and maintain randomization in clinical trials. Adaptive designs for discrete covariates and their asymptotic properties have been well studied in the literature. However, important continuous covariates are often involved in clinical studies. Simply disc...
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abstract::There is debate whether clinical trials with suboptimal power are justified and whether results from large studies are more reliable than the (combined) results of smaller trials. We quantified the error rates for evaluations based on single conventionally powered trials (80% or 90% power) versus evaluations based on ...
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abstract::In medical experiments with the objective of testing the equality of two means, data are often partially paired by design or because of missing data. The partially paired data represent a combination of paired and unpaired observations. In this article, we review and compare nine methods for analyzing partially paired...
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pub_type: 杂志文章,评审
doi:10.1177/0962280215577111
更新日期:2017-06-01 00:00:00
abstract::We propose a hierarchical Bayesian methodology to model spatially or spatio-temporal clustered survival data with possibility of cure. A flexible continuous transformation class of survival curves indexed by a single parameter is used. This transformation model is a larger class of models containing two special cases ...
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abstract::Most statistical developments in the joint modelling area have focused on the shared random-effect models that include characteristics of the longitudinal marker as predictors in the model for the time-to-event. A less well-known approach is the joint latent class model which consists in assuming that a latent class s...
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doi:10.1177/0962280212445839
更新日期:2014-02-01 00:00:00
abstract::Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Po...
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pub_type: 杂志文章
doi:10.1177/0962280217749991
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abstract::The statistical analysis of genome-wide association studies (GWASs) with multiple diseases and shared controls (SCs) is discussed. The usual method for analyzing data from these studies is to compare each individual disease with either the SCs or the pooled controls which include other diseases. We observed that apply...
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doi:10.1177/0962280212474061
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doi:10.1177/0962280214560046
更新日期:2017-04-01 00:00:00
abstract::Purpose The prevalence estimates of binary variables in sample surveys are often subject to two systematic errors: measurement error and nonresponse bias. A multiple-bias analysis is essential to adjust for both biases. Methods In this paper, we linked the latent class log-linear and proxy pattern-mixture models to ad...
journal_title:Statistical methods in medical research
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doi:10.1177/0962280217690939
更新日期:2018-10-01 00:00:00
abstract:BACKGROUND:When trials are subject to departures from randomised treatment, simple statistical methods that aim to estimate treatment efficacy, such as per protocol or as treated analyses, typically introduce selection bias. More appropriate methods to adjust for departure from randomised treatment are rarely employed,...
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doi:10.1177/0962280217735560
更新日期:2019-03-01 00:00:00
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pub_type: 杂志文章,评审
doi:10.1191/0962280204sm352ra
更新日期:2004-02-01 00:00:00
abstract::Increasing the clinical applicability of functional neuroimaging technology is an emerging objective, e.g. for diagnostic and treatment purposes. We propose a novel Bayesian spatial hierarchical framework for predicting follow-up neural activity based on an individual's baseline functional neuroimaging data. Our appro...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212448972
更新日期:2013-08-01 00:00:00
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doi:10.1177/0962280215615899
更新日期:2018-01-01 00:00:00
abstract::Appropriate handling of aggregate missing outcome data is necessary to minimise bias in the conclusions of systematic reviews. The two-stage pattern-mixture model has been already proposed to address aggregate missing continuous outcome data. While this approach is more proper compared with the exclusion of missing co...
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