A composite likelihood approach to predict the sex of the baby.

Abstract:

:Couples with diseases associated with the sexual chromosomes, as well as families in countries where the desire for a male is extreme, are interested in influencing the sex of the baby. We propose an original composite likelihood approach to analyse the relation between sex of the newborn and timing of the intercourse which leads to conception. Although there exist numerous works on this relation, only few studies have been carried out on independent datasets to validate the existing theories. Since the sex of the newborn is only known in case of conception, the full likelihood of the data is not easily defined without strong assumptions. A composite likelihood is a pseudo likelihood defined as the product of likelihood functions relative to subsets of the data. In particular, we consider two such likelihoods, one modelling the day-specific probabilities of conception and the other modelling the sex of the newborn given a conception has occurred. The methodology is applied to a dataset from a European fecundability study. The results show no significant dependence of the sex of the newborn on the time of intercourse. The method developed may be applied to other situations when data are affected by selective sampling.

journal_name

Stat Methods Med Res

authors

Tiberi S,Scarpa B,Sartori N

doi

10.1177/0962280217702415

subject

Has Abstract

pub_date

2018-11-01 00:00:00

pages

3386-3396

issue

11

eissn

0962-2802

issn

1477-0334

journal_volume

27

pub_type

杂志文章
  • A proof-of-concept-to-confirmatory multiple adaptation design in the development of an anti-viral treatment.

    abstract::In the clinical development of some new infectious disease drugs, early clinical pharmacology trials may predict with high confidence that the efficacious doses are well below the range of the safety margin. In this case, a dose-ranging study may be unnecessary after a proof-of-concept (PoC) study testing the highest ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218807950

    authors: Fan XF,Gallo P,Su G,Menton R,Segal F

    更新日期:2019-12-01 00:00:00

  • Controlling for localised spatio-temporal autocorrelation in long-term air pollution and health studies.

    abstract::Estimating the long-term health impact of air pollution using an ecological spatio-temporal study design is a challenging task, due to the presence of residual spatio-temporal autocorrelation in the health counts after adjusting for the covariate effects. This autocorrelation is commonly modelled by a set of random ef...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214527384

    authors: Lee D,Mitchell R

    更新日期:2014-12-01 00:00:00

  • Optimal quantile level selection for disease classification and biomarker discovery with application to electrocardiogram data.

    abstract::Classification with a large number of predictors and biomarker discovery become increasingly important in biological and medical research. This paper focuses on performing classification of cardiovascular diseases based on electrocardiogram analysis which deals with many variables and a lot of measurements within vari...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217699996

    authors: Zhou Y,Huang R,Yu S,Ma Y

    更新日期:2018-11-01 00:00:00

  • Modelling of zero-inflation improves inference of metagenomic gene count data.

    abstract::Metagenomics enables the study of gene abundances in complex mixtures of microorganisms and has become a standard methodology for the analysis of the human microbiome. However, gene abundance data is inherently noisy and contains high levels of biological and technical variability as well as an excess of zeros due to ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218811354

    authors: Jonsson V,Österlund T,Nerman O,Kristiansson E

    更新日期:2019-12-01 00:00:00

  • Propensity scores: from naive enthusiasm to intuitive understanding.

    abstract::Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often carried out via outcome regression modelling. An alternative approach is to use propensity score methodology. The propensity score is the conditional probability of receiving the exposure given the observed covariates a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280210394483

    authors: Williamson E,Morley R,Lucas A,Carpenter J

    更新日期:2012-06-01 00:00:00

  • Correcting for dependent censoring in routine outcome monitoring data by applying the inverse probability censoring weighted estimator.

    abstract::Censored data make survival analysis more complicated because exact event times are not observed. Statistical methodology developed to account for censored observations assumes that patients' withdrawal from a study is independent of the event of interest. However, in practice, some covariates might be associated to b...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216628900

    authors: Willems S,Schat A,van Noorden MS,Fiocco M

    更新日期:2018-02-01 00:00:00

  • Joint modeling of longitudinal zero-inflated count and time-to-event data: A Bayesian perspective.

    abstract::Longitudinal zero-inflated count data are encountered frequently in substance-use research when assessing the effects of covariates and risk factors on outcomes. Often, both the time to a terminal event such as death or dropout and repeated measure count responses are collected for each subject. In this setting, the l...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216659312

    authors: Zhu H,DeSantis SM,Luo S

    更新日期:2018-04-01 00:00:00

  • Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

    abstract::Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cl...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217708654

    authors: NeCamp T,Kilbourne A,Almirall D

    更新日期:2017-08-01 00:00:00

  • Stochastic models of sequence evolution including insertion-deletion events.

    abstract::Comparison of sequences that have descended from a common ancestor based on an explicit stochastic model of substitutions, insertions and deletions has risen to prominence in the last decade. Making statements about the positions of insertions-deletions (abbr. indels) is central in sequence and genome analysis and is ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280208099500

    authors: Miklós I,Novák A,Satija R,Lyngsø R,Hein J

    更新日期:2009-10-01 00:00:00

  • A test of inflated zeros for Poisson regression models.

    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...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217749991

    authors: He H,Zhang H,Ye P,Tang W

    更新日期:2019-04-01 00:00:00

  • A transformation class for spatio-temporal survival data with a cure fraction.

    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 ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212445658

    authors: Hurtado Rúa SM,Dey DK

    更新日期:2016-02-01 00:00:00

  • Applications of temporal kernel canonical correlation analysis in adherence studies.

    abstract::Adherence to medication is often measured as a continuous outcome but analyzed as a dichotomous outcome due to lack of appropriate tools. In this paper, we illustrate the use of the temporal kernel canonical correlation analysis (tkCCA) as a method to analyze adherence measurements and symptom levels on a continuous s...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280215598805

    authors: John M,Lencz T,Ferbinteanu J,Gallego JA,Robinson DG

    更新日期:2017-10-01 00:00:00

  • The application of methods to quantify attributable risk in medical practice.

    abstract::Several epidemiological parameters have been introduced for quantifying the population impact of a certain exposure on morbidity on a population level, termed 'attributable risk' (AR). Of these definitions, the AR as suggested by Levin in 1953 or some algebraic transformations of it are most commonly used. A structure...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/096228020101000305

    authors: Uter W,Pfahlberg A

    更新日期:2001-06-01 00:00:00

  • Promoting structural effects of covariates in the cure rate model with penalization.

    abstract::Cure rate models have been widely adopted for characterizing survival data that have long-term survivors. Under a mixture cure rate model where the population is a mixture of cured and susceptible subjects, a primary goal is to study covariate effects on the cure probability and survival function of the susceptible su...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217708684

    authors: Fan X,Liu M,Fang K,Huang Y,Ma S

    更新日期:2017-10-01 00:00:00

  • Small sample sizes: A big data problem in high-dimensional data analysis.

    abstract::In many experiments and especially in translational and preclinical research, sample sizes are (very) small. In addition, data designs are often high dimensional, i.e. more dependent than independent replications of the trial are observed. The present paper discusses the applicability of max t-test-type statistics (mu...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220970228

    authors: Konietschke F,Schwab K,Pauly M

    更新日期:2020-11-24 00:00:00

  • Latent mixture models for multivariate and longitudinal outcomes.

    abstract::Repeated measures and multivariate outcomes are an increasingly common feature of trials. Their joint analysis by means of random effects and latent variable models is appealing but patterns of heterogeneity in outcome profile may not conform to standard multivariate normal assumptions. In addition, there is much inte...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/0962280209105016

    authors: Pickles A,Croudace T

    更新日期:2010-06-01 00:00:00

  • A stochastic estimation procedure for intermittently-observed semi-Markov multistate models with back transitions.

    abstract::Multistate models provide an important method for analyzing a wide range of life history processes including disease progression and patient recovery following medical intervention. Panel data consisting of the states occupied by an individual at a series of discrete time points are often used to estimate transition i...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217736342

    authors: Aralis H,Brookmeyer R

    更新日期:2019-03-01 00:00:00

  • Designs in partially controlled studies: messages from a review.

    abstract::The ability to evaluate effects of factors on outcomes is increasingly important for studies that control some but not all of the factors. Although important advances have been made in methods of analysis for such partially controlled studies, work on designs has been limited. To help understand why, we review the mai...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1191/0962280205sm405oa

    authors: Li F,Frangakis CE

    更新日期:2005-08-01 00:00:00

  • Forensic inference from genetic markers.

    abstract::This review provides an overview of forensic inference from genetic markers. Because the judge and jurors are charged with decision-making, the forensic expert's job is to provide a useful summary of the evidence to the court. Hence, this review focuses on the likelihood ratio as a means of summarizing the genetic dat...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029300200304

    authors: Devlin B

    更新日期:1993-01-01 00:00:00

  • Predicting brain activity using a Bayesian spatial model.

    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

    authors: Derado G,Bowman FD,Zhang L,Alzheimer's Disease Neuroimaging Initiative Investigators.

    更新日期:2013-08-01 00:00:00

  • Measuring agreement in method comparison studies.

    abstract::Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differenc...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029900800204

    authors: Bland JM,Altman DG

    更新日期:1999-06-01 00:00:00

  • Estimating the effect of treatment on binary outcomes using full matching on the propensity score.

    abstract::Many non-experimental studies use propensity-score methods to estimate causal effects by balancing treatment and control groups on a set of observed baseline covariates. Full matching on the propensity score has emerged as a particularly effective and flexible method for utilizing all available data, and creating well...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280215601134

    authors: Austin PC,Stuart EA

    更新日期:2017-12-01 00:00:00

  • A curvilinear bivariate random changepoint model to assess temporal order of markers.

    abstract::In biomedical research, various longitudinal markers measuring different quantities are often collected over time. For example, repeated measures of psychometric scores are very informative about the degradation process toward dementia. These trajectories are generally nonlinear with an acceleration of the decline a f...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219898719

    authors: Segalas C,Helmer C,Jacqmin-Gadda H

    更新日期:2020-09-01 00:00:00

  • Checking linearity of non-parametric component in partially linear models with an application in systemic inflammatory response syndrome study.

    abstract::Two tests are proposed for checking the linearity of nonparametric function in partially linear models. The first one is based on a Crámer-von Mises statistic. This test can detect the local alternative converging to the null at the parametric rate 1/square root n. A bootstrap resample technique is provided to calcula...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1191/0962280206sm440oa

    authors: Liang H

    更新日期:2006-06-01 00:00:00

  • A multiphase non-linear mixed effects model: An application to spirometry after lung transplantation.

    abstract::In medical sciences, we often encounter longitudinal temporal relationships that are non-linear in nature. The influence of risk factors may also change across longitudinal follow-up. A system of multiphase non-linear mixed effects model is presented to model temporal patterns of longitudinal continuous measurements, ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214537255

    authors: Rajeswaran J,Blackstone EH

    更新日期:2017-02-01 00:00:00

  • Advanced colorectal neoplasia risk stratification by penalized logistic regression.

    abstract::Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratif...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280213497432

    authors: Lin Y,Yu M,Wang S,Chappell R,Imperiale TF

    更新日期:2016-08-01 00:00:00

  • Unbiasedness and efficiency of non-parametric and UMVUE estimators of the probabilistic index and related statistics.

    abstract::In reliability theory, diagnostic accuracy, and clinical trials, the quantity P ( X > Y ) + ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220966629

    authors: Verbeeck J,Deltuvaite-Thomas V,Berckmoes B,Burzykowski T,Aerts M,Thas O,Buyse M,Molenberghs G

    更新日期:2020-12-01 00:00:00

  • Separating variability in healthcare practice patterns from random error.

    abstract::Improving the quality of care that patients receive is a major focus of clinical research, particularly in the setting of cardiovascular hospitalization. Quality improvement studies seek to estimate and visualize the degree of variability in dichotomous treatment patterns and outcomes across different providers, where...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217754230

    authors: Thomas LE,Schulte PJ

    更新日期:2019-04-01 00:00:00

  • The asymptotic maximal procedure for subject randomization in clinical trials.

    abstract::The maximal procedure is a restricted randomization method that maximizes the number of feasible allocation sequences under the constraints of the maximum tolerated imbalance and the allocation sequence length. It assigns an equal probability to all feasible sequences. However, its implementation is not easy due to th...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216677107

    authors: Zhao W,Berger VW,Yu Z

    更新日期:2018-07-01 00:00:00

  • Prospective analysis of infectious disease surveillance data using syndromic information.

    abstract::In this paper, we describe a Bayesian hierarchical Poisson model for the prospective analysis of data for infectious diseases. The proposed model consists of two components. The first component describes the behavior of disease during nonepidemic periods and the second component represents the increase in disease coun...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214527385

    authors: Corberán-Vallet A,Lawson AB

    更新日期:2014-12-01 00:00:00