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PubMed2006

Longitudinal formant analysis after cochlear implantation in school-aged children.

INTRODUCTION: The purpose of this investigation was to describe the correlation between vocal and hearing development by longitudinal analysis of sound spectrograms, as a basic system for evaluating progress in vocal development. SUBJECTS AND METHODS: Two school-aged children with prelingual deafness were evaluated diachronically to assess speech perception and speech intelligibility after cochlear implantation. One child had non-syndromic hearing impairment without any known neurological deficit except for hearing loss, while the other had hearing impairment accompanied by mild mental retardation and attention deficit disorder. Their voices were recorded for monthly follow-up after cochlear implantation; these were used for formant analysis and compared with their mother's voice, and alteration of the formant data was also compared with monosyllable speech perception. RESULTS: Formant analysis demonstrated high concordance was observed between monosyllable speech perception and speech intelligibility. F1-F2 forms of the patients more closely resembled those of their mothers after 1 year's follow-up. The time point at which speech development altered was very similar in both cases although the final outcomes were different. CONCLUSION: Fair improvement of articulation after cochlear implant was demonstrated by the F1-F2 gram analysis. This procedure can be used for data sharing and cooperation between medical and educational specialists.

Child↗
PubMed2002

Brain atrophy in mild or moderate traumatic brain injury: a longitudinal quantitative analysis.

BACKGROUND AND PURPOSE: Although mild or moderate traumatic brain injury (TBI) is known to cause persistent neurologic sequelae, the underlying structural changes remain elusive. Our purpose was to assess decreases in the volume of brain parenchyma (VBP) in patients with TBI and to determine if clinical parameters are predictors of the extent of atrophy. METHODS: We retrospectively assessed the total VBP in 14 patients with mild or moderate TBI at more than 3 months after injury and in seven patients at two time points more than 3 months apart. VBP was calculated from whole-brain MR images and then normalized by calculating the percent VBP (%VBP) to correct for intraindividual variations in cranial size. Clinical parameters at the time of trauma were evaluated for potential predictors of atrophy. Findings were compared with those of control subjects of similar ages. RESULTS: In the single time-point analysis, brain volumes, CSF volumes, and %VBP were not significantly different between patients and control subjects. In the longitudinal analysis, the rate of decline in %VBP (0.02 versus 0.0064 U/day, P =.05) and the change in %VBP between the first and second time points (-4.16 +/- 1.68 versus -1.49 +/- 1.7, P =.022 [mean +/-SD]) were significantly greater in patients. Change in %VBP was significantly greater in patients with loss of consciousness (LOC) than in those without LOC (P =.023). CONCLUSION: Whole-brain atrophy occurs after mild or moderate TBI and is evident at an average of 11 months after trauma. Injury that produces LOC leads to more atrophy. These findings may help elucidate an etiology for the persistent or new neurologic deficits that occur months after injury.

Adult↗
PubMed2004

Mixed effects multivariate adaptive splines model for the analysis of longitudinal and growth curve data.

In this article, I review the use of nonparametric methods in the analysis of longitudinal and growth curve data, particularly the multivariate adaptive splines models for the analysis of longitudinal data (MASAL). These methods combine nonparametric techniques (B-splines, kernel smoothing, piecewise polynomials) and models with random effects, and provide fruitful alternatives to mixed effects linear models. Similarities, differences, strengths and limitations among these methods are presented. The analysis of a real example is also presented to illustrate the application and interpretation of MASAL. Open questions are posed for further investigation.

Biomedical Research↗
PubMed1992

Statistical analysis of longitudinal quality of life data with missing measurements.

The statistical analysis of longitudinal quality of life data in the presence of missing data is discussed. In cancer trials missing data are generated due to the fact that patients die, drop out, or are censored. These missing data are problematic in the monitoring of the quality of life during the trial. However, by means of assuming that the cause of the missing data lies in the observed history of the patients and not in their unobserved future, the missing data are ignorable. Consequently, all available data can be used to estimate quality of life change patterns with time. The computations that are required are illustrated with real quality of life data and three commonly used computer packages for statistical analysis.

Analysis of Variance↗
PubMed2004

The effect of aging on functional decline among older Japanese living in a community: a 5-year longitudinal data analysis.

BACKGROUND AND AIMS: Using longitudinal data analyses, we examined the effects of aging on functional decline, based on activities of daily living (ADL) and instrumental activities of daily living (IADL) during a 5-year follow-up among older people living in a community in Japan. METHODS: The baseline survey in July 1988 involved all elderly residents aged 60 or older in Saku City, Nagano, Japan (N=13418). All survivors of this cohort were asked to participate in follow-up surveys conducted in 1989, 1990, 1991, 1992 and 1993. Five items of ADL and five of IADL were measured on each survey. A generalized estimating equations (GEE) analysis was used to examine the effects of aging on the increase of the proportion of subjects with functional dependence. RESULTS: These results indicated that the proportion of subjects who were dependent in ADL increased during the 5-year period by 2.2 times (p<0.001) and the proportion of those who were dependent in either ADL or IADL increased during the same period by 1.8 times (p<0.001). Gender did not appear to be significantly associated with functional decline. CONCLUSIONS: The GEE analysis in this study identified the statistically significant effect of aging on the increase of the proportion of subjects with functional dependence based on ADL and IADL.

Activities of Daily Living↗
PubMed2004

The causal ordering of mathematics anxiety and mathematics achievement: a longitudinal panel analysis.

Using data from the Longitudinal Study of American Youth (LSAY), we aimed to determine the causal ordering between mathematics anxiety and mathematics achievement. Results of structural equation modelling showed that, across the entire junior and senior high school, prior low mathematics achievement significantly related to later high mathematics anxiety, but prior high mathematics anxiety hardly related to later low mathematics achievement. Mathematics achievement was more reliably stable from year to year than mathematics anxiety. There were statistically significant gender differences in the causal ordering between mathematics anxiety and mathematics achievement. Prior low mathematics achievement significantly related to later high mathematics anxiety for boys across the entire junior and senior high school but for girls at critical transition points only. Mathematics anxiety was more reliably stable from year to year among girls than among boys.

Anxiety↗
PubMedDate not supplied

Smoking behaviour and biological maturation in males and females: a 20-year longitudinal study. Analysis of data from the Amsterdam Growth and Health Longitudinal Study.

PRIMARY OBJECTIVE: (1) Describe the longitudinal smoking behaviour of boys and girls during adolescence in relation to calendar age, skeletal age, years from peak height velocity (PHV) and years from menarche (in girls). (2) and (3) Investigate the timing of biological maturation (early or late maturation) in relation to smoking behaviour in adolescence and in adulthood (i.e. calendar age 32/33). HPOTHESIS: We hypothesized skeletal age, years from PHV and years from menarche to be better predictors of smoking than calendar age. RESEARCH DESIGN: This study is part of the Amsterdam Growth and Health Longitudinal Study (AGAHLS) that was started in 1977 with 619 pupils from two secondary schools (mean age 13.0 SD 0.6). METHODS AND PROCEDURES: Smoking behaviour was assessed four times between 1977 and 1980 and once in 1996/1997. Calendar age and skeletal age were measured annually whereas height and menarche were measured every 4 months. Maturation rate (skeletal age minus calendar age), age at PHV and age at menarche were used to estimate timing of biological maturation. Generalized Estimating Equation (GEE) analysis was used to study maturation rate in relation to smoking during adolescence, whereas logistic regression analyses were used to study mean maturation rate, years from PHV and years from menarche in relation to smoking in adulthood. OUTCOME AND RESULTS: Skeletal age, years from PHV and years from menarche are no better predictors of smoking during adolescence than calendar age. The prevalence of smoking rises gradually with the increase in all four estimates of biological maturation. Timing of biological maturation was positively related to smoking but only at calendar age 13 (OR 3.34, CI 1.58, 7.07). None of the three measures to estimate timing of biological maturation was significantly related to smoking status in adulthood.

Adolescent↗
PubMed2000

Analysis of longitudinal substance use outcomes using ordinal random-effects regression models.

In this paper we describe analysis of longitudinal substance use outcomes using random-effects regression models (RRM). Some of the advantages of this approach is that these models allow for incomplete data across time, time-invariant and time-varying covariates, and can estimate individual change across time. Because substance use outcomes are often measured in terms of dichotomous or ordinal categories, our presentation focuses on categorical versions of RRM. Specifically, we present and describe an ordinal RRM that includes the possibility that covariate effects vary across the cutpoints of the ordinal outcome. This latter feature is particularly useful because a treatment can have varying effects on full versus partial abstinence, for example. Data from a smoking cessation study are used to illustrate application of this model for analysis of longitudinal substance use data.

Humans↗
PubMedDate not supplied

[Multilevel model applications to the analysis of longitudinal data].

This work is an introduction to repeated measurement analysis for longitudinal studies. It uses a two stage modelling framework, using hierarchical linear models with two levels. The first level pertains to the repeated measures, the second level pertains to the individual. For the last 25 years, hierarchical linear models have been used in the Social Sciences to analyse data coming from organizations with multiple levels. Their applications have been extended to the study of change in populations, both to describe the average change in an outcome variable in a population and to analyse the factors associated with variability in the individual trajectories of change. In this article, the basic concepts are introduced: between subjects and within subjects variability, the person-specific model for the individual trajectory and the between person model to describe how individuals vary in their trajectories, fixed and random effects, linear and quadratic growth models. At the end of each section, an illustration is given for the study of cognitive function of the older people cohort "Aging in Leganés", followed in four occasions between 1993 and 1999. Results from fitting the models to answer the most frequently asked research questions in the descriptions and analysis of individual change are presented. Lastly, we present possible generalizations of these linear models to non linear situations which arise when outcomes are dichotomous, nominal or ordinal.

Aging↗
PubMed2006

A method for fitting regression splines with varying polynomial order in the linear mixed model.

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

Blood Pressure Monitoring, Ambulatory↗
PubMed2006

Survival analysis of longitudinal microarrays.

MOTIVATION: The development of methods for linking gene expressions to various clinical and phenotypic characteristics is an active area of genomic research. Scientists hope that such analysis may, for example, describe relationships between gene function and clinical events such as death or recovery. Methods are available for relating gene expression to measurements that are categorized or continuous, but there is less work in relating expressions to an observed event time such as time to death, response or relapse. When gene expressions are measured over time, there are methods for differentiating temporal patterns. However, methods have not yet been proposed for the survival analysis of longitudinally collected microarrays. RESULTS: We describe an approach for the survival analysis of longitudinal gene expression data. We construct a measure of association between the time to an event and gene expressions collected over time. Statistical significance is addressed using permutations and control of the false discovery rate. Our proposed method is illustrated on a dataset from a multi-center research study of inflammation and response to injury that aims to uncover the biological reasons why patients can have dramatically different outcomes after suffering a traumatic injury (www.gluegrant.org).

Algorithms↗
PubMed2004

Analysis of longitudinal studies with death and drop-out: a case study.

The analysis of longitudinal data has recently been an active area of biostatistical research. Two main approaches to analysis have emerged, the first concentrating on modelling evolution of marginal distributions of the main response variable of interest and the other on subject-specific trajectories. In epidemiology the analysis is usually complicated by missing data and by death of study participants. Motivated by a study of cognitive decline in the elderly, this paper argues that these two types of incomplete follow-up may need to be treated differently in the analysis, and proposes an extension to the marginal modelling approach. The problem of informative drop-out is also discussed. The methods are implemented in the 'Stata' statistical package.

Age Factors↗
PubMed2006

Herpes simplex virus 2 infection increases HIV acquisition in men and women: systematic review and meta-analysis of longitudinal studies.

OBJECTIVE: To estimate the sex-specific effect of herpes simplex virus type 2 (HSV-2) on the acquisition of HIV infection. BACKGROUND: The increased number of longitudinal studies available since the last meta-analysis was published allows for the calculation of age- and sexual behaviour-adjusted relative risks (RR) separately for men and women. DESIGN: Systematic review and meta-analysis of longitudinal studies. METHODS: PubMed, Embase and relevant conference abstracts were systematically searched to identify longitudinal studies in which the relative timing of HSV-2 infection and HIV infection could be established. Where necessary, authors were contacted for separate estimates in men and women, adjusted for age and a measure of sexual behaviour. Summary adjusted RR were calculated using random-effects meta-analyses where appropriate. Studies on recent HSV-2 incidence as a risk factor for HIV acquisition were also collated. RESULTS: Of 19 eligible studies identified, 18 adjusted for age and at least one measure of sexual behaviour after author contact. Among these, HSV-2 seropositivity was a statistically significant risk factor for HIV acquisition in general population studies of men [summary adjusted RR, 2.7; 95% confidence interval (CI), 1.9-3.9] and women (RR, 3.1; 95% CI, 1.7-5.6), and among men who have sex with men (RR, 1.7; 95% CI, 1.2-2.4). The effect in high-risk women showed significant heterogeneity, with no overall evidence of an association. CONCLUSIONS: Prevalent HSV-2 infection is associated with a three-fold increased risk of HIV acquisition among both men and women in the general population, suggesting that, in areas of high HSV-2 prevalence, a high proportion of HIV is attributable to HSV-2.

Female↗
PubMed1986

Longitudinal data analysis for discrete and continuous outcomes.

Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.

Child↗
PubMed1991

Longitudinal Gompertzian analysis of prostate cancer mortality in the U.S., 1962-1987: a method of demonstrating relative environmental, genetic and competitive influences upon mortality.

Age-specific mortality rates for prostate cancer (PC) in the United States from 1962 to 1987 were subjected to longitudinal Gompertzian analysis. Age-specific PC mortality rate distributions between age 55 and 85 years were determined by a variable competitive factor and a common intersect point. The intersect point for PC occurred at age 61.5 years and mortality rate 27.9 per 100,000 and reflects genetic and environmental influences upon mortality. Between 1962 and 1987, non-age-standardized annual crude PC mortality rates increased 41.6%. Longitudinal Gompertzian analysis suggests that rising PC mortality rates in the United States are the natural consequence of competitive deterministic mortality dynamics. Moreover, longitudinal Gompertzian analysis is a method that demonstrates the relative contribution of environmental, genetic and competitive influences upon disease specific mortality.

Age Factors↗
PubMed2004

The dynamics of Wuchereria bancrofti infection: a model-based analysis of longitudinal data from Pondicherry, India.

This paper presents a model-based analysis of longitudinal data describing the impact of integrated vector management on the intensity of Wuchereria bancrofti infection in Pondicherry, India. The aims of this analysis were (1) to gain insight into the dynamics of infection, with emphasis on the possible role of immunity, and (2) to develop a model that can be used to predict the effects of control. Using the LYMFASIM computer simulation program, two models with different types of immunity (anti-L3 larvae or anti-adult worm fecundity) were compared with a model without immunity. Parameters were estimated by fitting the models to data from 5071 individuals with microfilaria-density measurement before and after cessation of a 5-year vector management programme. A good fit, in particular of the convex shape of the age-prevalence curve, required inclusion of anti-L3 or anti-fecundity immunity in the model. An individual's immune-responsiveness was found to halve in approximately 10 years after cessation of boosting. Explanation of the large variation in Mf-density required considerable variation between individuals in exposure and immune responsiveness. The mean life-span of the parasite was estimated at about 10 years. For the post-control period, the models predict a further decline in Mf prevalence, which agrees well with observations made 3 and 6 years after cessation of the integrated vector management programme.

Adolescent↗
PubMed2000

Subgroups of children with autism by cluster analysis: a longitudinal examination.

OBJECTIVES: A hierarchical cluster analysis was conducted using a sample of 138 school-age children with autism. The objective was to examine (1) the characteristics of resulting subgroups, (2) the relationship of these subgroups to subgroups of the same children determined at preschool age, and (3) preschool variables that best predicted school-age functioning. METHOD: Ninety-five cases were analyzed. RESULTS: Findings support the presence of 2 subgroups marked by different levels of social, language, and nonverbal ability, with the higher group showing essentially normal cognitive and behavioral scores. The relationship of high- and low-functioning subgroup membership to levels of functioning at preschool age was highly significant. CONCLUSIONS: School-age functioning was strongly predicted by preschool cognitive functioning but was not strongly predicted by preschool social abnormality or severity of autistic symptoms. The differential outcome of the 2 groups shows that high IQ is necessary but not sufficient for optimal outcome in the presence of severe language impairment.

Autistic Disorder↗
PubMed2004

Insulin-like growth factor-1, insulin-like growth factor binding protein-3, and cardiovascular disease risk factors in young black men and white men: the CARDIA Male Hormone Study.

Cross-sectional studies have found associations between components of the insulin-like growth factor (IGF) system and hypertension, total cholesterol, and low density lipoprotein cholesterol. Using partial correlation analysis and longitudinal analysis of data collected at the year 2, year 7, and year 10 examinations, the authors assessed the associations of IGF-1 and IGF binding protein-3 (IGFBP-3) with cardiovascular disease risk factors in 544 Black and 747 White male participants in the Coronary Artery Risk Development in Young Adults (CARDIA) Male Hormone Study who were aged 20-34 years at year 2 (1987-1988). There were no consistent independent associations with blood pressure. Cross-sectionally, there were some inverse associations between IGF-1 and lipid levels in White men (strongest r = -0.095 (p = 0.02) for total cholesterol at year 7) and positive associations between IGFBP-3 and lipid levels in Black and White men (for log(triglycerides), r = 0.072-0.136). Longitudinally, a 1,000-ng/ml increase in IGFBP-3 was associated with 3.7-mg/dl and 2.6-mg/dl higher total cholesterol levels and 2.6-mg/dl and 1.7-mg/dl higher low density lipoprotein cholesterol levels in Black men and White men (p < 0.05), respectively. These findings do not support a strong link between IGF-1 and IGFBP-3 and blood pressure, but they do support the possibility of important relations between IGFBP-3 and lipid levels in young adult men.

Adult↗