Finite mixture regression model with random effects: application to neonatal hospital length of stay

A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

The net benefit of saving the Asian elephant: a policy and contingent valuation study

Reports results from a contingent valuation (CV) survey of willingness to pay (WTP) for the conservation of the Asian elephant of a sample of urban residents living in three selected housing schemes in Colombo, the capital of Sri Lanka. Face-to-face surveys were conducted using an interview schedule (IS). A non-linear logit regression model is used to analyse the respondents' responses for the payment principle questions and to identify the factors that influence their responses. We investigate whether urban residents' WTP for the conservation of elephants is sufficient to compensate farmers for the damage caused by elephants. We find that the beneficiaries (the urban residents) could compensate losers (the fanners in the areas affected by human-elephant conflict, HEC) and be better off than in the absence of elephants in Sri Lanka. Therefore, there is a strong economic case for the conservation of the wild elephant population in Sri Lanka. However, we have insufficient data to determine the optimal level of this elephant population in the Kaldor-Hicks sense. Nevertheless, the current population of elephant in Sri Lanka is Kaldor-Hicks preferable to having none. (C) 2003 Elsevier B.V. All rights reserved.

Determinants of exercise capacity in patients with type 2 diabetes

OBJECTIVE - Type 2 diabetes is associated with reduced exercise capacity, but the cause of this association is unclear. We sought the associations of impaired exercise capacity in type 2 diabetes. RESEARCH DESIGN AND METHODS - Subclinical left ventricular (LV) dysfunction was sought from myocardial strain rate and the basal segmental diastolic velocity (Em) of each wall in 170 patients with type 2 diabetes (aged 56 +/- 10 years, 91 men), good quality echocardiographic images, and negative exercise echocardiograms. The same measurements were made in 56 control subjects (aged 53 +/- 10 years, 29 men). Exercise capacity was calculated in metabolic equivalents, and heart rate recovery (HRR) was measured as the heart rate difference between peak and 1 min after exercise. In subjects with type 2 diabetes, exercise capacity was correlated with clinical, therapeutic, biochemical, and echocardiographic variables, and significant independent associations were sought using a multiple linear regression model. RESULTS - Exercise capacity, strain rate, Em, and HRR were significantly reduced in type 2 diabetes. Exercise capacity was associated with age (r- = -0.37, P < 0.001), male sex (r = 0.26, P = 0.001), BMI (r = -0.19, P = 0.012), HbA(1c) (AlC; r = -0.22, P = 0.009), Em (r = 0.43, P < 0.001), HRR (r = 0.42, P < 0.001), diabetes duration (r = -0.18, P = 0.021), and hypertension history (r = -0.28, P < 0.001). Age (P < 0.001), male sex (P = 0.007), BMI (P = 0.001), Em (P = 0.032), HRR (P = 0.013), and AlC (P = 0.0007) were independent predictors of exercise capacity. CONCLUSIONS - Reduced exercise capacity in patients with type 2 diabetes is associated with diabetes control, subclinical LV dysfunction, and impaired HRR.

Rank test of location optimal for hyperbolic secant distribution

There are at least two reasons for a symmetric, unimodal, diffuse tailed hyperbolic secant distribution to be interesting in real-life applications. It displays one of the common types of non normality in natural data and is closely related to the logistic and Cauchy distributions that often arise in practice. To test the difference in location between two hyperbolic secant distributions, we develop a simple linear rank test with trigonometric scores. We investigate the small-sample and asymptotic properties of the test statistic and provide tables of the exact null distribution for small sample sizes. We compare the test to the Wilcoxon two-sample test and show that, although the asymptotic powers of the tests are comparable, the present test has certain practical advantages over the Wilcoxon test.

Benthic metabolism as an indicator of stream ecosystem health

We tested direct and indirect measures of benthic metabolism as indicators of stream ecosystem health across a known agricultural land-use disturbance gradient in southeast Queensland, Australia. Gross primary production (GPP) and respiration (R-24) in benthic chambers in cobble and sediment habitats, algal biomass (as chlorophyll a) from cobbles and sediment cores, algal biomass accrual on artificial substrates and stable carbon isotope ratios of aquatic plants and benthic sediments were measured at 53 stream sites, ranging from undisturbed subtropical rainforest to catchments where improved pasture and intensive cropping are major land-uses. Rates of benthic GPP and R-24 varied by more than two orders of magnitude across the study gradient. Generalised linear regression modelling explained 80% or more of the variation in these two indicators when sediment and cobble substrate dominated sites were considered separately, and both catchment and reach scale descriptors of the disturbance gradient were important in explaining this variation. Model fits were poor for net daily benthic metabolism (NDM) and production to respiration ratio (P/R). Algal biomass accrual on artificial substrate and stable carbon isotope ratios of aquatic plants and benthic sediment were the best of the indirect indicators, with regression model R-2 values of 50% or greater. Model fits were poor for algal biomass on natural substrates for cobble sites and all sites. None of these indirect measures of benthic metabolism was a good surrogate for measured GPP. Direct measures of benthic metabolism, GPP and R-24, and several indirect measures were good indicators of stream ecosystem health and are recommended in assessing process-related responses to riparian and catchment land use change and the success of ecosystem rehabilitation actions.

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

Optimal crossover designs for logistic regression models in pharmacodynamics

Pharmacodynamics (PD) is the study of the biochemical and physiological effects of drugs. The construction of optimal designs for dose-ranging trials with multiple periods is considered in this paper, where the outcome of the trial (the effect of the drug) is considered to be a binary response: the success or failure of a drug to bring about a particular change in the subject after a given amount of time. The carryover effect of each dose from one period to the next is assumed to be proportional to the direct effect. It is shown for a logistic regression model that the efficiency of optimal parallel (single-period) or crossover (two-period) design is substantially greater than a balanced design. The optimal designs are also shown to be robust to misspecification of the value of the parameters. Finally, the parallel and crossover designs are combined to provide the experimenter with greater flexibility.