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At least 127 records · Page 7Linked to original sources
PubMed2005

Psychotropic combination in schizophrenia.

OBJECTIVE: To study adjunctive medications used with antipsychotic agents in schizophrenia via comparisons of antidepressant, anxiolytic and antiparkinsonian co-prescribing. METHOD: In the context of a national naturalistic prospective observational study, a database containing all the prescriptions from 100 French psychiatrists during the year 2002 was analysed. The inclusion criteria were a diagnosis of schizophrenia or schizoaffective disorder and age over 18. A log-linear model and generalised linear mixed models were used. RESULTS: In all 5,257 prescriptions for 922 patients were analysed. The proportion of patients who were prescribed an antiparkinsonian drug was 32.9%. Amisulpride, haloperidol, phenothiazines with a sedative action and depot typical antipsychotics proved more likely to be prescribed with antiparkinsonians. The frequency of antidepressant and anxiolytic prescriptions was 51.2% and 52.3%, respectively. Associations between atypical antipsychotics (except clozapine) and antidepressants were positive while associations between typical antipsychotics and antidepressants were not. There were no differences among antipsychotics for the prescription of anxiolytics. CONCLUSIONS: Atypical antipsychotics can be expected to be less likely associated with antiparkinsonians. This result is indeed found for olanzapine, clozapine and to a limited extent for risperidone. Furthermore, a trend towards a positive association between atypical antipsychotics and antidepressants appears. In view of the antidepressive action of certain atypical antipsychotics, this result is surprising. The increase in the prescriptions of anxiolytics concerns all types of antipsychotics. In view of the increase in associated medications in schizophrenia and the difficulty of estimating it in randomised trials, this study underlines the contribution of naturalistic studies on this score.

Adult↗
PubMed2006

Associations between Neospora caninum specific antibodies in serum and milk in two dairy herds in Scotland.

The study evaluated the use of the Mastazyme ELISA for quantification of Neospora caninum (N. caninum) specific IgG in bovine milk and examined the relationship between serum and milk antibodies in two dairy herds. The serum and milk antibodies both had bimodal distributions in each herd. This was mainly due to between cow variation: in both herds, approximately two thirds of cows were either clearly and consistently seropositive or seronegative for N. caninum with one third consistently near the threshold. Milk and serum N. caninum IgG were strongly related. This relationship was modelled using a linear mixed model including a polynomial term for serum, the effect of herd, and between and within cow variance components. The latter gave a significantly better fit to the data than a model that allowed for a different relationship for the positive and negative (according to the serum test) groups of observations. The sensitivity and specificity (based on serum percentage positivity (pp)) of the milk antibody was determined for different milk pp thresholds. In spite of the differences between the relationship of milk to serum seen for the two herds, for those estimates with sufficient precision, sensitivity and specificity greater than 0.73 for both herds were obtained using single thresholds of 14 and 15.5 for milk pp in both herds based on, as our gold standard, serum antibody pp thresholds of 22.5 and 25, respectively. If milk antibody is to be used for detecting persistently infected cows, the higher threshold of 15.5 may be suitable while for epidemiological screening 14 would be preferable. Further validation in a greater number of herds is required, but our results suggest that this test may prove to be a useful adjunct to serum N. caninum IgG assays in the monitoring of N. caninum infection as part of herd health programmes and epidemiological studies.

Abortion, Veterinary↗
PubMed2002

Spatio-temporal modelling of rates for the construction of disease maps.

There have been significant developments in disease mapping in the past few decades. The continual development of statistical methodology in this area is responsible for the growing popularity of disease mapping because of its potential usefulness in regional health planning, disease surveillance and intervention, and allocating health funding. Here we review the area of disease mapping where relative risks pertain to an event such as incidence or mortality over space and time. In particular we briefly discuss the use of generalized additive mixed models, an additive extension of generalized linear mixed models, for spatio-temporal analysis of disease rates. To illustrate the procedures, we present an in-depth analysis of infant mortality data in the province of British Columbia, Canada. The goals of the analysis are to produce more reliable small-area estimates of mortality rates, assess spatial patterns over time, and examine risk trends at both global (provincial) and local (local health area) levels.

British Columbia↗
PubMed2001

Analysis of nucleotide sequence data using mixed model methodology.

Linear, logistic, and multivariate mixed model analyses were applied to simulated data of five quantitative traits and a binary liability trait to detect associations with sequence variants in seven genes. Infrequent site variants (< 1%) were eliminated and conservative step-wise procedures were used to reduce the number of variants fitted. Random effects accounting for additive genetic relationships between individuals and for common environment effects were fitted to reduce spurious significant results. Five sites in genes 1, 2, and 6 had significant effects (p < 0.0001) on the traits and were found in both replicates studied. Survival analysis using a Weibull model identified two significant sites for disease age at onset. Other less significant sites may be false positives or due to founder effects. This approach was effective in identifying putative sites while accounting for polygenic and environmental sources of variation.

Genetic Predisposition to Disease↗
PubMed2007

Latent-variable models for longitudinal data with bivariate ordinal outcomes.

We use the concept of latent variables to derive the joint distribution of bivariate ordinal outcomes, and then extend the model to allow for longitudinal data. Specifically, we relate the observed ordinal outcomes using threshold values to a bivariate latent variable, which is then modelled as a linear mixed model. Random effects terms are used to tie all together repeated observations from the same subject. The cross-sectional association between the two outcomes is modelled through the correlation coefficient of the bivariate latent variable, conditional on random effects. Assuming conditional independence given random effects, the marginal likelihood, under the missing data at random assumption, is approximated using an adaptive Gaussian quadrature for numerical integration. The model provides fixed effects parameters that are subject-specific, but retain the population-averaged interpretation when properly scaled. This is particularly well suited for the situation in which population comparisons and individual level contrasts are of equal importance. Data from a psychiatric trial, the Fluvoxamine (an antidepressant drug) study, are used to illustrate the methodology.

Antidepressive Agents, Second-Generation↗
PubMed1995

Meta-analysis: weighing the evidence.

Use of meta-analytical (quantitative overview) techniques is now commonplace in a wide range of medical research contexts, with a rapid rise in its frequency of use being particularly apparent in the last decade. The history of meta-analyses in other fields, particularly psychology and educational research, is longer. Many methods have been proposed and used, from crude 'vote counting' of studies showing significant or non-significant results, through methods for combination of effect size estimates based on fixed or random effects models, to general linear mixed models and Bayesian methods. The history of meta-analysis and the advantages and disadvantages of various approaches to it are briefly reviewed in this paper, with reference to pharmaceutical product licence applications, other reviews of clinical trials and epidemiological studies, and health services research.

Bayes Theorem↗
PubMed2024

Detecting inbreeding depression in structured populations.

Measuring inbreeding and its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However, there is no consensus on the best method, neither for quantification of inbreeding itself nor for the model to estimate its effect on specific traits. We simulated traits based on simulated genomes from a large pedigree and empirical whole-genome sequences of human data from populations with various sizes and structures (from the 1,000 Genomes project). We compare the ability of various inbreeding coefficients ([Formula: see text]) to quantify the strength of inbreeding depression: allele-sharing, two versions of the correlation of uniting gametes which differ in the weight they attribute to each locus and two identical-by-descent segments-based estimators. We also compare two models: the standard linear model and a linear mixed model (LMM) including a genetic relatedness matrix (GRM) as random effect to account for the nonindependence of observations. We find LMMs give better results in scenarios with population or family structure. Within the LMM, we compare three different GRMs and show that in homogeneous populations, there is little difference among the different [Formula: see text] and GRM for inbreeding depression quantification. However, as soon as a strong population or family structure is present, the strength of inbreeding depression can be most efficiently estimated only if i) the phenotypes are regressed on [Formula: see text] based on a weighted version of the correlation of uniting gametes, giving more weight to common alleles and ii) with the GRM obtained from an allele-sharing relatedness estimator.

Humans↗
PubMedDate not supplied

Meta-analysis and the synthesis of evidence.

Use of meta-analytical (quantitative overview) techniques is now commonplace in a large range of medical-research contexts, with a rapid rise in its frequency of use being particularly apparent in the last decade. Many methods of meta-analysis have been proposed and used, from crude 'vote-counting' of studies showing significant or nonsignificant results, through methods for combination of effect-size estimates based on fixed- or random-effects models, to general, linear, mixed models and Bayesian methods. The history of meta-analysis and the advantages and disadvantages of various approaches to it are briefly reviewed in this paper, with reference to its application in health-services research and related fields. Broader approaches to the synthesis of evidence in these contexts using conventional multilevel modelling and hierarchical Bayesian models to address the combination of evidence from disparate types of study are then outlined.

Bayes Theorem↗
PubMed2003

A local influence approach applied to binary data from a psychiatric study.

Recently, a lot of concern has been raised about assumptions needed in order to fit statistical models to incomplete multivariate and longitudinal data. In response, research efforts are being devoted to the development of tools that assess the sensitivity of such models to often strong but always, at least in part, unverifiable assumptions. Many efforts have been devoted to longitudinal data, primarily in the selection model context, although some researchers have expressed interest in the pattern-mixture setting as well. A promising tool, proposed by Verbeke et al. (2001, Biometrics 57, 43-50), is based on local influence (Cook, 1986, Journal of the Royal Statistical Society, Series B 48, 133-169). These authors considered the Diggle and Kenward (1994, Applied Statistics 43, 49-93) model, which is based on a selection model, integrating a linear mixed model for continuous outcomes with logistic regression for dropout. In this article, we show that a similar idea can be developed for multivariate and longitudinal binary data, subject to nonmonotone missingness. We focus on the model proposed by Baker, Rosenberger, and DerSimonian (1992, Statistics in Medicine 11, 643-657). The original model is first extended to allow for (possibly continuous) covariates, whereafter a local influence strategy is developed to support the model-building process. The model is able to deal with nonmonotone missingness but has some limitations as well, stemming from the conditional nature of the model parameters. Some analytical insight is provided into the behavior of the local influence graphs.

Antidepressive Agents, Tricyclic↗
PubMed2004

Genetic analysis of non-essential amino acid contents in rice (Oryza sativa L.) across environments.

Genetic main effects and genotype x environment (GE) interaction effects for 7 non-essential amino acids in milled rice were analyzed for two year data by using the genetic models based on mixed linear model approaches for quantitative traits of triploid endosperm. Nine cytoplasmic, male sterile lines as females and five restoring lines as males were introduced in a diallel cross in two environments. It was found that the content of non-essential amino acids including Asp, Ser, Glu, Gly and Tyr were mainly controlled by genetic main effects, whereas the content of Ala or Pro was mainly affected by GE effects. In genetic main effects, the cytoplasmic and maternal genetic effects were preponderant for all traits of non-essential amino acids, indicating that selection for improving these traits based on the maternal plant would be more effective than on seeds. The total narrow-sense heritabilities for non-essential amino acids were 70.9-85.9%. By predicating the genetic effects of parents, the total genetic effects from Xieqingzao, V20, Zuo 5 and Zhenshan 97 were mainly negative and these parents would decrease the content of most essential amino acids. Since parents of Zhenan 3, Yinchao 1, T49, 26715, 102 and 1391 had possessed a positive value of most total genetic effects, these parents could be chosen as optimal parents for increasing the content of most non-essential amino acids.

Amino Acids↗
PubMed1999

Assessing the goodness-of-fit of the Laird and Ware model--an example: the Jimma Infant Survival Differential Longitudinal Study.

The Jimma Infant Survival Differential Longitudinal Study is an Ethiopian study, set up to establish risk factors affecting infant survival and to investigate socio-economic, maternal and infant-rearing factors that contribute most to the child's early survival. Here, a subgroup of about 1500 children born in Jimma town is examined for their first year's weight gain. Of special interest is the impact of certain cultural practices like uvulectomy, milk teeth extraction and butter swallowing, on child's weight gain; these have never been thoroughly investigated in any study. In this context, the linear mixed model (Laird and Ware) is employed. The purpose of this paper is to illustrate the practical issues when constructing the longitudinal model. Recently developed diagnostics will be used herefor. Finally, special attention will be paid to the two-stage interpretation of the linear mixed model.

Adult↗
PubMed1998

A mixed model for repeated dilution assays.

We propose a generalized linear mixed model to estimate and test marginal effects on titers repeatedly measured by serial dilution assays. The link is log-log and the titer is assumed to follow a gamma distribution. The parameters are estimated by generalized estimating equations. The marginal effects are tested by means of Wald and score tests, using the robust estimator of the variance. This approach avoids the problems arising from assays leading to nonestimable individual titers. Simulations were used to compare the Wald and score tests to Wilcoxon and Student t-tests. This method is applied to the comparison of the antiviral efficiency of three treatments against HIV.

Anti-HIV Agents↗
PubMed2006

A nonlinear model with latent process for cognitive evolution using multivariate longitudinal data.

Cognition is not directly measurable. It is assessed using psychometric tests, which can be viewed as quantitative measures of cognition with error. The aim of this article is to propose a model to describe the evolution in continuous time of unobserved cognition in the elderly and assess the impact of covariates directly on it. The latent cognitive process is defined using a linear mixed model including a Brownian motion and time-dependent covariates. The observed psychometric tests are considered as the results of parameterized nonlinear transformations of the latent cognitive process at discrete occasions. Estimation of the parameters contained both in the transformations and in the linear mixed model is achieved by maximizing the observed likelihood and graphical methods are performed to assess the goodness of fit of the model. The method is applied to data from PAQUID, a French prospective cohort study of ageing.

Aged↗
PubMed2002

Repeated measures models for prescribing change.

Linear mixed models are used to detect a change, if any, in prescribing habits at the primary care practice level due to an educational intervention given repeated measures data before and after intervention and a control group. Inferences are corrected for general practice size, fundholding status and baseline prescribing. The correlation structure is discussed and the results for multilevel modelling using MLwiN and NLME version 3.0 are compared.

Anti-Inflammatory Agents, Non-Steroidal↗
PubMed2006

A predictive model for postoperative intraocular pressure among patients undergoing laser in situ keratomileusis (LASIK).

PURPOSE: The aim of this study was to develop a predictive model based on preoperative variables for estimating postoperative intraocular pressure (IOP) of those eyes undergoing LASIK surgery, to predict the amount of underestimated IOP after LASIK for myopia and myopic astigmatism. DESIGN: Pretest-post-test longitudinal study. METHODS: Both eyes of 193 eligible subjects who underwent LASIK procedures at the Department of Ophthalmology, National Taiwan University Hospital, from July 2000 to December 2002 for myopia and myopic astigmatism were identified to build up the predictive models. IOPs were measured with noncontact air-puff tonometry. Information on age, gender, preoperative central corneal thickness (CCT), preoperative central corneal curvature (CCK), preoperative spherical equivalent refractive error, and ablation depth was collected and applied for predicting postoperative IOP after LASIK based on linear mixed model. RESULTS: Significant predictors for postoperative IOP after myopic LASIK procedures included age, gender, preoperative IOP, ablation depth, preoperative CCT, and preoperative spherical equivalent refractive errors. The linear mixed model, taking into account these significant preoperative correlates and the correlation of IOPs between both eyes of the same patient, explained 91% of the variation of postoperative IOP. CONCLUSIONS: A statistical model was developed for predicting the amount of underestimated IOP after LASIK for myopia and myopic astigmatism, which is of clinical importance to uncover ocular hypertension among patients whose information on postoperative IOP immediately after LASIK is not available.

Adult↗
PubMed2002

Quality of life in advanced non-small-cell lung cancer: results of a Southwest Oncology Group randomized trial.

PURPOSE: The main purpose of this paper is to present the results of a randomized trial comparing the effects of two chemotherapy regimens on the Quality of life (QOL) of patients with advanced non-small-cell lung cancer (NSCLC). Trials in advanced stage disease represent an important treatment context for QOL assessment. A second purpose of this paper is to examine methods for handling the level of missing data commonly observed in the advanced stage disease context. METHODS: Patients were randomized to receive cisplatin plus vinorelbine or carboplatin plus paclitaxel. The QOL of 222 patients was assessed with the Functional Assessment of Cancer Therapy-Lung (FACT-L) prior to randomization; follow-up assessments occurred at 13 and 25 weeks. Three methods were used to analyze the QOL data: (1) cross-sectional analysis of four patient categories (improved, stable, missing, and declined) based on changes in the FACT-L score, (2) a mixed linear model, and (3) a pattern mixture model. The longitudinal analyses addressed two potential data biases. RESULTS: Questionnaire submission rates were 91% at baseline, 68% at 13 weeks, and 47% at 25 weeks. The cross-sectional and mixed linear model analyses did not show significant differences by treatment arm in patient-reported QOL. The pattern mixture model analysis, more appropriate given non-ignorable missing data, also found no statistically significant effect of treatment on patient QOL. CONCLUSION: We present a sensitivity analysis approach with multiple methods for analyzing treatment effects on patient QOL in the presence of substantial, non-ignorable missing data in an advanced stage disease clinical trial. We conclude that the two treatment arms did not differ statistically in their effects on patient QOL over a 25-week treatment period.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2006

Ambulatory pulse pressure and progression of urinary albumin excretion in older patients with type 2 diabetes mellitus.

We studied whether ambulatory blood pressure monitoring added to office blood pressure in predicting progression of urine albumin excretion over 2 years of follow-up in a multiethnic cohort of older people with type-2 diabetes mellitus. Participants in the Informatics for Diabetes Education and Telemedicine study underwent a baseline evaluation that included office and 24-hour ambulatory blood pressure measurement and a spot urine measurement of albumin-to-creatinine ratio (ACR). Measurements of albumin-to-creatinine ratio were repeated 1 and 2 years later. In bivariate analyses, ambulatory 24-hour pulse pressure was the blood pressure variable most strongly associated with follow-up ACR. Repeated-measures mixed linear models (n = 1040) were built adjusting for baseline ACR ratio, clustered randomization, time to follow-up, and multiple covariates. When both were entered into the model, ambulatory 24-hour pulse pressure and office pulse pressure were independently associated with follow-up ACR (beta [SE] = 0.010 [0.002], P < 0.001, and 0.004 [0.001], P = 0.002, respectively). Cox proportional hazards models examined associations with progression of albuminuria in 954 participants without macroalbuminuria at baseline, adjusting for all of the covariates independently associated with follow-up ACR in mixed linear models. Ambulatory 24-hour pulse pressure, but not office pulse pressure, was independently associated with progression of albuminuria (P = 0.015 and 0.052, respectively). The adjusted hazards ratio (95% CI) per each 10-mm Hg increment in ambulatory pulse pressure was 1.23 (1.04 to 1.42). In conclusion, ambulatory pulse pressure may provide additional information to predict progression of albuminuria in elderly diabetic subjects above and beyond office blood pressure.

Aged↗
PubMed1997

Construction of hearing percentiles in women with non-constant variance from the linear mixed-effects model.

Current age-specific reference standards for adult hearing thresholds are primarily cross-sectional in nature and vary in the degree of screening of the reference sample for noise-induced hearing loss and other hearing problems. We develop methods to construct age-specific percentiles for longitudinal data that have been modelled using the linear mixed-effects model. We apply these methods to construct percentiles of hearing level using data from a carefully screened sample of women from the Baltimore Longitudinal Study of Aging. However, the variation in the residuals and random effects from the linear mixed-effects model does not remain constant with age and frequency of the stimulus tone. In addition, the distribution of the hearing levels is not symmetric about the mean. We develop a number of methods to use the output from the linear mixed-effects model to construct percentiles that do not have constant variance. We use a transformation of the hearing levels to provide for skewness in the final percentile curves. The change in the variation of the residuals and random effects is modelled as a function of beginning age and frequency and we use this variance function to construct the hearing percentiles. We present a number of approaches. First, we use the absolute values of the population residuals to model the total deviation about the mean as a function of beginning age and frequency. Second, we model the standard deviation in the person-specific (cluster) residuals as well as the standard deviation in the estimated random effects. Finally, we use weighted least squares with the regressions on the absolute cluster residuals and absolute estimated random effects where the weights are the reciprocal of the standard deviations of their estimates.

Adolescent↗