Longitudinal Measurements (longitudinal + measurement)

Distribution by Scientific Domains


Selected Abstracts


New Powerful Approaches for Family-based Association Tests with Longitudinal Measurements

ANNALS OF HUMAN GENETICS, Issue 1 2009
Xiao Ding
Summary We discuss several new powerful family-based approaches for testing genetic association when the traits are obtained from longitudinal or repeated measurement studies. The popular approach FBAT-PC is based on a linear combination of the individual traits. We propose a one-sided modification, FBAT-PCM, which has a closed-form expression and is always more powerful. We also present two approaches FBAT-LC and FBAT-LCC based on linear combination of the univariate test statistics. Furthermore, all three approaches are shown to be unified to a general form. Through simulation studies, we compare the power of these tests under different models of genetic effect sizes. Compared to original FBAT-PC, our modification achieves a power gain of up to 50%. In addition, all three new approaches gain substantial power compared to the ordinary approach of Bonferroni correction, with the relative performance depending upon the underlying model. Application of these approaches for testing an association between Body Mass Index and a previously reported candidate SNP confirms our results. [source]


Robust Joint Modeling of Longitudinal Measurements and Competing Risks Failure Time Data

BIOMETRICAL JOURNAL, Issue 1 2009
Ning Li
Abstract Existing methods for joint modeling of longitudinal measurements and survival data can be highly influenced by outliers in the longitudinal outcome. We propose a joint model for analysis of longitudinal measurements and competing risks failure time data which is robust in the presence of outlying longitudinal observations during follow-up. Our model consists of a linear mixed effects sub-model for the longitudinal outcome and a proportional cause-specific hazards frailty sub-model for the competing risks data, linked together by latent random effects. Instead of the usual normality assumption for measurement errors in the linear mixed effects sub-model, we adopt a t -distribution which has a longer tail and thus is more robust to outliers. We derive an EM algorithm for the maximum likelihood estimates of the parameters and estimate their standard errors using a profile likelihood method. The proposed method is evaluated by simulation studies and is applied to a scleroderma lung study (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]


On Estimating the Relationship between Longitudinal Measurements and Time-to-Event Data Using a Simple Two-Stage Procedure

BIOMETRICS, Issue 3 2010
Paul S. Albert
SummaryYe, Lin, and Taylor (2008,,Biometrics,64, 1238,1246) proposed a joint model for longitudinal measurements and time-to-event data in which the longitudinal measurements are modeled with a semiparametric mixed model to allow for the complex patterns in longitudinal biomarker data. They proposed a two-stage regression calibration approach that is simpler to implement than a joint modeling approach. In the first stage of their approach, the mixed model is fit without regard to the time-to-event data. In the second stage, the posterior expectation of an individual's random effects from the mixed-model are included as covariates in a Cox model. Although Ye et al. (2008) acknowledged that their regression calibration approach may cause a bias due to the problem of informative dropout and measurement error, they argued that the bias is small relative to alternative methods. In this article, we show that this bias may be substantial. We show how to alleviate much of this bias with an alternative regression calibration approach that can be applied for both discrete and continuous time-to-event data. Through simulations, the proposed approach is shown to have substantially less bias than the regression calibration approach proposed by Ye et al. (2008). In agreement with the methodology proposed by Ye et al. (2008), an advantage of our proposed approach over joint modeling is that it can be implemented with standard statistical software and does not require complex estimation techniques. [source]


Conditional Estimation for Generalized Linear Models When Covariates Are Subject-Specific Parameters in a Mixed Model for Longitudinal Measurements

BIOMETRICS, Issue 1 2004
Erning Li
Summary. The relationship between a primary endpoint and features of longitudinal profiles of a continuous response is often of interest, and a relevant framework is that of a generalized linear model with covariates that are subject-specific random effects in a linear mixed model for the longitudinal measurements. Naive implementation by imputing subject-specific effects from individual regression fits yields biased inference, and several methods for reducing this bias have been proposed. These require a parametric (normality) assumption on the random effects, which may be unrealistic. Adapting a strategy of Stefanski and Carroll (1987, Biometrika74, 703,716), we propose estimators for the generalized linear model parameters that require no assumptions on the random effects and yield consistent inference regardless of the true distribution. The methods are illustrated via simulation and by application to a study of bone mineral density in women transitioning to menopause. [source]


Knee-heel length measurements in preterm infants: evaluation of a simple electronically equipped instrument

ACTA PAEDIATRICA, Issue 2 2003
E Engström
Aim: To compare and evaluate a mini-knemometer with a simple and inexpensive electronic caliper with regard to precision, handling error (technical error) and estimation of growth velocity. Methods: Thirty-five prematurely born infants, with a median gestational age of 29 (range 24,33) wk and a median birthweight of 960 (range 480,2480) g, were measured on 409 different occasions with both instruments. On each occasion, five independent readings were made. Results: There was no significant difference in precision between the two instruments, when measuring growth velocity over a 4 wk period (median 0.41, range 0.10,0.59 mm d,1). The handling error in this study, calculated as the mean standard deviation, was 0.36 (SD 0.18, coefficient of variation 0.38%) mm for the simple electronic caliper and 0.59 mm for the mini-knemometer. Short-term growth was detectable within 2 d when growth velocity was normal. Conclusion: Longitudinal measurement of lower leg length is a gentle and useful complementary method for assessing growth in preterm infants. An inexpensive electronic caliper is well suited for routine use in clinical practice, with measurements taken once or twice a week. [source]


Dose,time,response modeling of longitudinal measurements for neurotoxicity risk assessment

ENVIRONMETRICS, Issue 6 2005
Yiliang Zhu
Abstract Neurotoxic effects are an important non-cancer endpoint in health risk assessment and environmental regulation. Neurotoxicity tests such as neurobehavioral screenings using a functional observational battery generate longitudinal dose,response data to profile neurological effects over time. Analyses of longitudinal neurotoxicological data have mostly relied on analysis of variance; explicit dose,time,response modeling has not been reported in the literature. As dose,response modeling has become an increasingly indispensible component in risk assessment as required by the use of benchmark doses, there are strong interests in and needs for appropriate dose,response models, effective model-fitting techniques, and computation methods for benchmark dose estimation. In this article we propose a family of dose,time,response models, illustrate statistical inference of these models in conjunction with random-effects to quantify inter-subject variation, and describe a procedure to profile benchmark dose across time. We illustrate the methods through a dataset from a US/EPA experiment involving the FOB tests on rats administered to a single dose of triethyl tin (TET). The results indicate that the existing functional observational battery data can be utilized for dose,response and benchmark dose analyses and the methods can be applied in general settings of neurotoxicity risk assessment. Copyright © 2005 John Wiley & Sons, Ltd. [source]


Monitoring nutritional status accurately and reliably in adolescents with anorexia nervosa

JOURNAL OF PAEDIATRICS AND CHILD HEALTH, Issue 1-2 2009
Andrew C Martin
Aim: Accurate assessment of nutritional status is a vital aspect of caring for individuals with anorexia nervosa (AN) and body mass index (BMI) is considered an appropriate and easy to use tool. Because of the intense fear of weight gain, some individuals may attempt to mislead the physician. Mid-upper arm circumference (MUAC) is a simple, objective method of assessing nutritional status. The setting is an eating disorders clinic in a tertiary paediatric hospital in Western Australia. The aim of this study is to evaluate how well MUAC correlates with BMI in adolescents with AN. Methods: Prospective observational study to evaluate nutritional status in adolescents with AN. Results: Fifty-five adolescents aged 12,17 years with AN were assessed between January 1, 2004 and January 1, 2006. MUAC was highly correlated with BMI (r = 0.79, P < 0.001) and individuals with MUAC ,20 cm rarely required hospitalisation (negative predictive value 93%). Conclusions: MUAC reflects nutritional status as defined by BMI in adolescents with AN. Lack of consistency between longitudinal measurements of BMI and MUAC should be viewed suspiciously and prompt a more detailed nutritional assessment. [source]


Soluble cellular adhesion molecules, selectins, VEGF and endothelin-1 in patients with Wuchereria bancrofti infection and association with clinical status

PARASITE IMMUNOLOGY, Issue 1-2 2005
P. Esterre
SUMMARY Lymphatic filariasis, a mosquito-transmitted disease commonly known as Bancroftian filariasis, is characterized by debilitating pathology linked to the progression of lymphoedema to a chronic state of elephantiasis. We performed longitudinal measurements of endothelial adhesion and angiogenic molecules in 63 Polynesian patients living in an hyperendemic focus of Wuchereria bancrofti. Decreased serum concentrations of soluble (s-) L selectin (CD62L) were noticed in sera of of patients with chronic conditions (hydrocele and elephantiasis). Chyluria was associated with increased vascular endothelial growth factor (VEGF) levels, whereas elephantiasis presented a high endothelin-1 (ET-1) profile. By contrast, increased serum concentrations of soluble intercellular (sICAM-1, CD54), but not of vascular cell (sVCAM-1, CD106), adhesion molecules were observed in sera of patients with bacterial lymphangitis used as controls. These trends are consistent with the increased permeability of vascular structures, a major clinical feature observed in acute lymphatic pathology (of bacterial or filarial origin), and of fundamental differences in the pathogenesis of hydrocele and elephantiasis. Using markers correlated with the clinical status (high ET-1 and VEGF levels for elephantiasis and chyluria, respectively; low CD62L levels for hydrocoele and elephantiasis) it should be possible to monitor disease progression in lymphatic filariasis. [source]


Robust Joint Modeling of Longitudinal Measurements and Competing Risks Failure Time Data

BIOMETRICAL JOURNAL, Issue 1 2009
Ning Li
Abstract Existing methods for joint modeling of longitudinal measurements and survival data can be highly influenced by outliers in the longitudinal outcome. We propose a joint model for analysis of longitudinal measurements and competing risks failure time data which is robust in the presence of outlying longitudinal observations during follow-up. Our model consists of a linear mixed effects sub-model for the longitudinal outcome and a proportional cause-specific hazards frailty sub-model for the competing risks data, linked together by latent random effects. Instead of the usual normality assumption for measurement errors in the linear mixed effects sub-model, we adopt a t -distribution which has a longer tail and thus is more robust to outliers. We derive an EM algorithm for the maximum likelihood estimates of the parameters and estimate their standard errors using a profile likelihood method. The proposed method is evaluated by simulation studies and is applied to a scleroderma lung study (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]


On Estimating the Relationship between Longitudinal Measurements and Time-to-Event Data Using a Simple Two-Stage Procedure

BIOMETRICS, Issue 3 2010
Paul S. Albert
SummaryYe, Lin, and Taylor (2008,,Biometrics,64, 1238,1246) proposed a joint model for longitudinal measurements and time-to-event data in which the longitudinal measurements are modeled with a semiparametric mixed model to allow for the complex patterns in longitudinal biomarker data. They proposed a two-stage regression calibration approach that is simpler to implement than a joint modeling approach. In the first stage of their approach, the mixed model is fit without regard to the time-to-event data. In the second stage, the posterior expectation of an individual's random effects from the mixed-model are included as covariates in a Cox model. Although Ye et al. (2008) acknowledged that their regression calibration approach may cause a bias due to the problem of informative dropout and measurement error, they argued that the bias is small relative to alternative methods. In this article, we show that this bias may be substantial. We show how to alleviate much of this bias with an alternative regression calibration approach that can be applied for both discrete and continuous time-to-event data. Through simulations, the proposed approach is shown to have substantially less bias than the regression calibration approach proposed by Ye et al. (2008). In agreement with the methodology proposed by Ye et al. (2008), an advantage of our proposed approach over joint modeling is that it can be implemented with standard statistical software and does not require complex estimation techniques. [source]


Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

BIOMETRICS, Issue 1 2010
Ying Yuan
Summary We study quantile regression (QR) for longitudinal measurements with nonignorable intermittent missing data and dropout. Compared to conventional mean regression, quantile regression can characterize the entire conditional distribution of the outcome variable, and is more robust to outliers and misspecification of the error distribution. We account for the within-subject correlation by introducing a,,2,penalty in the usual QR check function to shrink the subject-specific intercepts and slopes toward the common population values. The informative missing data are assumed to be related to the longitudinal outcome process through the shared latent random effects. We assess the performance of the proposed method using simulation studies, and illustrate it with data from a pediatric AIDS clinical trial. [source]


A Two-Part Joint Model for the Analysis of Survival and Longitudinal Binary Data with Excess Zeros

BIOMETRICS, Issue 2 2008
Dimitris Rizopoulos
Summary Many longitudinal studies generate both the time to some event of interest and repeated measures data. This article is motivated by a study on patients with a renal allograft, in which interest lies in the association between longitudinal proteinuria (a dichotomous variable) measurements and the time to renal graft failure. An interesting feature of the sample at hand is that nearly half of the patients were never tested positive for proteinuria (,1g/day) during follow-up, which introduces a degenerate part in the random-effects density for the longitudinal process. In this article we propose a two-part shared parameter model framework that effectively takes this feature into account, and we investigate sensitivity to the various dependence structures used to describe the association between the longitudinal measurements of proteinuria and the time to renal graft failure. [source]


Conditional Estimation for Generalized Linear Models When Covariates Are Subject-Specific Parameters in a Mixed Model for Longitudinal Measurements

BIOMETRICS, Issue 1 2004
Erning Li
Summary. The relationship between a primary endpoint and features of longitudinal profiles of a continuous response is often of interest, and a relevant framework is that of a generalized linear model with covariates that are subject-specific random effects in a linear mixed model for the longitudinal measurements. Naive implementation by imputing subject-specific effects from individual regression fits yields biased inference, and several methods for reducing this bias have been proposed. These require a parametric (normality) assumption on the random effects, which may be unrealistic. Adapting a strategy of Stefanski and Carroll (1987, Biometrika74, 703,716), we propose estimators for the generalized linear model parameters that require no assumptions on the random effects and yield consistent inference regardless of the true distribution. The methods are illustrated via simulation and by application to a study of bone mineral density in women transitioning to menopause. [source]


Evaluating the effect of the new alignment algorithm for longitudinal series of Heidelberg retina tomography images

ACTA OPHTHALMOLOGICA, Issue 2 2008
Ciara Bergin
Abstract. Purpose:, To evaluate the impact of a new image-alignment algorithm on the repeatability of longitudinal measurements obtained from Heidelberg retina tomograph (HRT) images. Methods:, HRTI and HRTII image series from 124 patients with glaucoma or ocular hypertension were made available from previously reported studies and were reprocessed with the old and new image-alignment algorithms. Improvements afforded by the new alignment algorithm were examined by considering statistically significant improvement in repeatability of specific stereometric parameters (SP), namely rim area (RA), rim volume (RV), cup volume (CV) and cup shape measure (CSM). A further comparison was made by examining reduction in the variability of pixel-by-pixel height measures within image series. Results:, In some HRT image series, the new algorithm automatically corrected obvious misalignment events that occurred with the previous algorithm. However, average improvement in repeatability of the SP in HRTI image series was not statistically significant (P = 0.13) and there was no statistically significant reduction in pixel-by-pixel height measurement variability (P =0.73). In HRTII image series, there was evidence of improvement, on average, in the repeatability of some parameters (RA, P = 0.01; RV, P = 0.02; CSM, P = 0.05), but not in CV (P = 0.22). There was a large reduction in pixel-by-pixel variability in HRTII image series (P,<,0.001). Conclusion:, There was no evidence to show that the new algorithm improved repeatability, on average, in HRTI images. However, the application of the new algorithm to HRTII image series marginally improved repeatability in stereometric measures and yielded a significant reduction in pixel-by-pixel variability. [source]