Interpolation between spatial frameworks: an application of process convolution to estimating neighbourhood disease prevalence.

Abstract:

:Health data may be collected across one spatial framework (e.g. health provider agencies), but contrasts in health over another spatial framework (neighbourhoods) may be of policy interest. In the UK, population prevalence totals for chronic diseases are provided for populations served by general practitioner practices, but not for neighbourhoods (small areas of circa 1500 people), raising the question whether data for one framework can be used to provide spatially interpolated estimates of disease prevalence for the other. A discrete process convolution is applied to this end and has advantages when there are a relatively large number of area units in one or other framework. Additionally, the interpolation is modified to take account of the observed neighbourhood indicators (e.g. hospitalisation rates) of neighbourhood disease prevalence. These are reflective indicators of neighbourhood prevalence viewed as a latent construct. An illustrative application is to prevalence of psychosis in northeast London, containing 190 general practitioner practices and 562 neighbourhoods, including an assessment of sensitivity to kernel choice (e.g. normal vs exponential). This application illustrates how a zero-inflated Poisson can be used as the likelihood model for a reflective indicator.

journal_name

Stat Methods Med Res

authors

Congdon P

doi

10.1177/0962280212447150

subject

Has Abstract

pub_date

2014-04-01 00:00:00

pages

169-82

issue

2

eissn

0962-2802

issn

1477-0334

pii

0962280212447150

journal_volume

23

pub_type

杂志文章
  • Mixture modelling for cluster analysis.

    abstract::Cluster analysis via a finite mixture model approach is considered. With this approach to clustering, the data can be partitioned into a specified number of clusters g by first fitting a mixture model with g components. An outright clustering of the data is then obtained by assigning an observation to the component to...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1191/0962280204sm372ra

    authors: McLachlan GJ,Chang SU

    更新日期:2004-10-01 00:00:00

  • Measurement error, time lag, unmeasured confounding: Considerations for longitudinal estimation of the effect of a mediator in randomised clinical trials.

    abstract::Clinical trials are expensive and time-consuming and so should also be used to study how treatments work, allowing for the evaluation of theoretical treatment models and refinement and improvement of treatments. These treatment processes can be studied using mediation analysis. Randomised treatment makes some of the a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216666111

    authors: Goldsmith KA,Chalder T,White PD,Sharpe M,Pickles A

    更新日期:2018-06-01 00:00:00

  • Bayesian modeling and prediction of accrual in multi-regional clinical trials.

    abstract::In multi-regional trials, the underlying overall and region-specific accrual rates often do not hold constant over time and different regions could have different start-up times, which combined with initial jump in accrual within each region often leads to a discontinuous overall accrual rate, and these issues associa...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214557581

    authors: Deng Y,Zhang X,Long Q

    更新日期:2017-04-01 00:00:00

  • A non-parametric model to address overdispersed count response in a longitudinal data setting with missingness.

    abstract::Count responses are becoming increasingly important in biostatistical analysis because of the development of new biomedical techniques such as next-generation sequencing and digital polymerase chain reaction; a commonly met problem in modeling them with the popular Poisson model is overdispersion. Although it has been...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280215583397

    authors: Zhang H,He H,Lu N,Zhu L,Zhang B,Zhang Z,Tang L

    更新日期:2017-06-01 00:00:00

  • A new approach to hierarchical data analysis: Targeted maximum likelihood estimation for the causal effect of a cluster-level exposure.

    abstract::We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and popula...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218774936

    authors: Balzer LB,Zheng W,van der Laan MJ,Petersen ML

    更新日期:2019-06-01 00:00:00

  • Maximum likelihood estimation based on Newton-Raphson iteration for the bivariate random effects model in test accuracy meta-analysis.

    abstract::A bivariate generalised linear mixed model is often used for meta-analysis of test accuracy studies. The model is complex and requires five parameters to be estimated. As there is no closed form for the likelihood function for the model, maximum likelihood estimates for the parameters have to be obtained numerically. ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219853602

    authors: Willis BH,Baragilly M,Coomar D

    更新日期:2020-04-01 00:00:00

  • Inferring the direction of a causal link and estimating its effect via a Bayesian Mendelian randomization approach.

    abstract::The use of genetic variants as instrumental variables - an approach known as Mendelian randomization - is a popular epidemiological method for estimating the causal effect of an exposure (phenotype, biomarker, risk factor) on a disease or health-related outcome from observational data. Instrumental variables must sati...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219851817

    authors: Bucur IG,Claassen T,Heskes T

    更新日期:2020-04-01 00:00:00

  • Correcting for non-participation bias in health surveys using record-linkage, synthetic observations and pattern mixture modelling.

    abstract::Surveys are key means of obtaining policy-relevant information not available from routine sources. Bias arising from non-participation is typically handled by applying weights derived from limited socio-demographic characteristics. This approach neither captures nor adjusts for differences in health and related behavi...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219854482

    authors: Gray L,Gorman E,White IR,Katikireddi SV,McCartney G,Rutherford L,Leyland AH

    更新日期:2020-04-01 00:00:00

  • Probability intervals of toxicity and efficacy design for dose-finding clinical trials in oncology.

    abstract::Immunotherapy, gene therapy or adoptive cell therapies, such as the chimeric antigen receptor+ T-cell therapies, have demonstrated promising therapeutic effects in oncology patients. We consider statistical designs for dose-finding adoptive cell therapy trials, in which the monotonic dose-response relationship assumed...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220977009

    authors: Lin X,Ji Y

    更新日期:2020-12-16 00:00:00

  • Exact one-sided confidence limits for Cohen's kappa as a measurement of agreement.

    abstract::Cohen's kappa coefficient, κ, is a statistical measure of inter-rater agreement or inter-annotator agreement for qualitative items. In this paper, we focus on interval estimation of κ in the case of two raters and binary items. So far, only asymptotic and bootstrap intervals are available for κ due to its complexity. ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214552881

    authors: Shan G,Wang W

    更新日期:2017-04-01 00:00:00

  • Evaluation of change in CD4+ cell counts in AIDS clinical trials.

    abstract::To evaluate the antiretroviral activity of antiretroviral agents and to compare the effects of two different antiretroviral agents, we propose a non-parametric mixed-effects model to investigate change of CD4+ counts. The proposed model and methods are applied to analyse the data from PACTG345 study. Population and in...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280206075524

    authors: Liang H

    更新日期:2008-04-01 00:00:00

  • Obtaining evidence by a single well-powered trial or several modestly powered trials.

    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 ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212461098

    authors: IntHout J,Ioannidis JP,Borm GF

    更新日期:2016-04-01 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

  • 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

  • Copas-like selection model to correct publication bias in systematic review of diagnostic test studies.

    abstract::The accuracy of a diagnostic test, which is often quantified by a pair of measures such as sensitivity and specificity, is critical for medical decision making. Separate studies of an investigational diagnostic test can be combined through meta-analysis; however, such an analysis can be threatened by publication bias....

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218791602

    authors: Piao J,Liu Y,Chen Y,Ning J

    更新日期:2019-10-01 00:00:00

  • A robust imputation method for missing responses and covariates in sample selection models.

    abstract::Sample selection arises when the outcome of interest is partially observed in a study. Although sophisticated statistical methods in the parametric and non-parametric framework have been proposed to solve this problem, it is yet unclear how to deal with selectively missing covariate data using simple multiple imputati...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217715663

    authors: Ogundimu EO,Collins GS

    更新日期:2019-01-01 00:00:00

  • Inferences about population means of health care costs.

    abstract::The analysis of health care costs is complicated by the skewed and heteroscedastic nature of their distribution with possibly additional zero values. Statistical methods that do not adjust for these features can lead to incorrect conclusions. This paper reviews recent developments in statistical methods for the analys...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1191/0962280202sm290ra

    authors: Zhou XH

    更新日期:2002-08-01 00:00:00

  • Model selection in multivariate semiparametric regression.

    abstract::Variable selection in semiparametric mixed models for longitudinal data remains a challenge, especially in the presence of multiple correlated outcomes. In this paper, we propose a model selection procedure that simultaneously selects fixed and random effects using a maximum penalized likelihood method with the adapti...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217690769

    authors: Li Z,Liu H,Tu W

    更新日期:2018-10-01 00:00:00

  • Joint latent class models for longitudinal and time-to-event data: a review.

    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...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/0962280212445839

    authors: Proust-Lima C,Séne M,Taylor JM,Jacqmin-Gadda H

    更新日期:2014-02-01 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

  • Interval estimation of a population mean using existing knowledge or data on effect sizes.

    abstract::Bayes or empirical Bayes methods to improve inferential accuracy for a population mean has been widely adopted in medical research. As the joint prior distribution of both the mean and variance parameters can be difficult to specify or estimate, most of these methods have relied on certain level of simplifications of ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218773537

    authors: Shen C

    更新日期:2019-06-01 00:00:00

  • Analysis of phase II methodologies for single-arm clinical trials with multiple endpoints in rare cancers: An example in Ewing's sarcoma.

    abstract::Trials run in either rare diseases, such as rare cancers, or rare sub-populations of common diseases are challenging in terms of identifying, recruiting and treating sufficient patients in a sensible period. Treatments for rare diseases are often designed for other disease areas and then later proposed as possible tre...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216662070

    authors: Dutton P,Love SB,Billingham L,Hassan AB

    更新日期:2018-05-01 00:00:00

  • Random-effects models for multivariate repeated measures.

    abstract::Mixed models are widely used for the analysis of one repeatedly measured outcome. If more than one outcome is present, a mixed model can be used for each one. These separate models can be tied together into a multivariate mixed model by specifying a joint distribution for their random effects. This strategy has been u...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280206075305

    authors: Fieuws S,Verbeke G,Molenberghs G

    更新日期:2007-10-01 00:00:00

  • Joint nested frailty models for clustered recurrent and terminal events: An application to colonoscopy screening visits and colorectal cancer risks in Lynch Syndrome families.

    abstract::Joint models for recurrent and terminal events have not been yet developed for clustered data. The goals of our study are to develop a statistical framework for modelling clustered recurrent and terminal events and to perform dynamic predictions of the terminal event in family studies. We propose a joint nested frailt...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219863076

    authors: Choi YH,Jacqmin-Gadda H,Król A,Parfrey P,Briollais L,Rondeau V

    更新日期:2020-05-01 00:00:00

  • Modeling fecundity in the presence of a sterile fraction using a semi-parametric transformation model for grouped survival data.

    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. co...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212438646

    authors: McLain AC,Sundaram R,Buck Louis GM

    更新日期:2016-02-01 00:00:00

  • A comparison of imputation strategies in cluster randomized trials with missing binary outcomes.

    abstract::In cluster randomized trials, clusters of subjects are randomized rather than subjects themselves, and missing outcomes are a concern as in individual randomized trials. We assessed strategies for handling missing data when analysing cluster randomized trials with a binary outcome; strategies included complete case, a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214530030

    authors: Caille A,Leyrat C,Giraudeau B

    更新日期:2016-12-01 00:00:00

  • Linear time-dependent reference intervals where there is measurement error in the time variable-a parametric approach.

    abstract::This article re-examines parametric methods for the calculation of time specific reference intervals where there is measurement error present in the time covariate. Previous published work has commonly been based on the standard ordinary least squares approach, weighted where appropriate. In fact, this is an incorrect...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280211426617

    authors: Gillard J

    更新日期:2015-12-01 00:00:00

  • Gene selection for survival data under dependent censoring: A copula-based approach.

    abstract::Dependent censoring arises in biomedical studies when the survival outcome of interest is censored by competing risks. In survival data with microarray gene expressions, gene selection based on the univariate Cox regression analyses has been used extensively in medical research, which however, is only valid under the ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214533378

    authors: Emura T,Chen YH

    更新日期:2016-12-01 00:00:00

  • Meta-analysis without study-specific variance information: Heterogeneity case.

    abstract::The random effects model in meta-analysis is a standard statistical tool often used to analyze the effect sizes of the quantity of interest if there is heterogeneity between studies. In the special case considered here, meta-analytic data contain only the sample means in two treatment arms and the sample sizes, but no...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217718867

    authors: Sangnawakij P,Böhning D,Niwitpong SA,Adams S,Stanton M,Holling H

    更新日期:2019-01-01 00:00:00

  • On adaptive propensity score truncation in causal inference.

    abstract::The positivity assumption, or the experimental treatment assignment (ETA) assumption, is important for identifiability in causal inference. Even if the positivity assumption holds, practical violations of this assumption may jeopardize the finite sample performance of the causal estimator. One of the consequences of p...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218774817

    authors: Ju C,Schwab J,van der Laan MJ

    更新日期:2019-06-01 00:00:00