Bayesian estimation of a random effects heteroscedastic probit model

Summary Bayesian analysis is given of a random effects binary probit model that allows for heteroscedasticity. Real and simulated examples illustrate the approach and show that ignoring heteroscedasticity when it exists may lead to biased estimates and poor prediction. The computation is carried out by an efficient Markov chain Monte Carlo sampling scheme that generates the parameters in blocks. We use the Bayes factor, cross‐validation of the predictive density, the deviance information criterion and Receiver Operating Characteristic (ROC) curves for model comparison.     

The estimation of moments: A technical note

The calculation of several common pharmacokinetic parameters requires estimates of both the area under the curve of the concentration of the drug in a sampled fluid vs. time, and also the first moment about t=0 of this area. It is proposed that the methods used to estimate these quantities should make consistent assumptions about the concentration of the drug. There appears to be an inconsistency in the standard published formulas in the case where concentration is interpolated linearly. A more consistent formula is derived.     

A note on the estimation of mixture models under endogenous sampling

Summary. The main purpose of this paper is to highlight that, in the estimation of mixture models under endogenous sampling, the distribution of the unobservables can be specified either in the actual population or in the artificial population induced by the sampling method. Which of the two approaches is correct depends crucially on the population of interest. The importance of making the correct decision is illustrated with a simple application.     

A note on non‐parametric estimation with predicted variables

Summary This article gives the asymptotic properties of non‐parametric kernel‐based density and regression estimators when one of the variables is predicted. Such variables, also known as ‘constructed variables’ or ‘generated predictors’, occur quite frequently in econometric and applied economic analysis. The impact of using predicted rather than observed values on the properties of estimators has been extensively studied in the fully parametric context. The results derived here are applicable to the general situation in which the predictor is estimated using a consistent non‐parametric method with standard convergence rates. Therefore, the presented results are, generally speaking, the asymptotics for semi‐non‐parametric two‐step (or plug‐in) estimation problems. The case of parametric estimation based on non‐parametric predictors is also covered.     

A note on a simple estimation of amphetamine, methylamphetamine and ephedrine in horse urine

A chromatographic separation of amphetamine, methylamphetamine and ephedrine from horse urine is possible on alkaline Silica Gel G plates developed with acetone-methanol (1:3). After elution, the bases are determined colorimetrically. The intensity of the violet colour resulting from the nitration of amphetamine is measured in a Unicam SP1300 colorimeter using filter No. 1 (sensitivity 50–250 μg). The colour produced by the interaction of methylamphetamine, sodium nitro-prusside, acetaldehyde and triethanolamine is measured at 590 mμ (sensitivity 200–2,000 μg). Ephedrine was determined by measuring the intensity of the brown colour of its dithiocarbamate at 440 mμ (sensitivity 100–900 μg).     

A note on the effects of changes in alcohol control policies in the Canadian North

Of three communities changing their alcohol control policies, only Frobisher Bay, the most isolated, experienced a noticeable decrease in arrests for assault and public drunkenness.     

The estimation of moments: a technical note

The calculation of several common pharmacokinetic parameters requires estimates of both the area under the curve of the concentration of the drug in a sampled fluid vs. time, and also the first moment about t = 0 of this area. It is proposed that the methods used to estimate these quantities should make consistent assumptions about the concentration of the drug. There appears to be an inconsistency in the standard published formulas in the case where concentration is interpolated linearly. A more consistent formula is derived.     

Biomarker variance component estimation for exposure surrogate selection and toxicokinetic inference

Biomarkers are useful exposure surrogates given their ability to integrate exposures through all routes and to reflect interindividual differences in toxicokinetic processes. Also, biomarker concentrations tend to vary less than corresponding environmental measurements, making them less-biasing surrogates for exposure. In this article, urinary PAH biomarkers (namely, urinary naphthalene [U-Nap]; urinary phenanthrene [U-Phe]; 1-hydroxypyrene [1-OH-Pyr]; and 1-, (2+3)-, 4-, and 9-hydroxyphenanthrene [1-, (2+3)-, 4-, and 9-OH-Phe]) were evaluated as surrogates for exposure to hot asphalt emissions using data from 20 road-paving workers. Linear mixed-effects models were used to estimate the within- and between-person components of variance for each urinary biomarker. The ratio of within- to between-person variance was then used to estimate the biasing effects of each biomarker on a theoretical exposure–response relationship. Mixed models were also used to estimate the amounts of variation in Phe metabolism to individual OH-Phe isomers that could be attributed to Phe exposure (as represented by U-Phe concentrations) and covariates representing time, hydration level, smoking status, age, and body mass index. Results showed that 1-OH-Phe, (2+3)-OH-Phe, and 1-OH-Pyr were the least-biasing surrogates for exposure to hot asphalt emissions, and that effects of hydration level and sample collection time substantially inflated bias estimates for the urinary biomarkers. Mixed-model results for the individual OH-Phe isomers showed that between 63% and 82% of the observed biomarker variance was collectively explained by Phe exposure, the time and day of sample collection, and the hydration level, smoking status, body mass index, and age of each worker. By difference, the model results also showed that, depending on the OH-Phe isomer, a maximum of 6–23% of the total biomarker variance was attributable to differences in unobserved toxicokinetic processes between the workers. Therefore, toxicokinetic processes are probably less influential on urinary biomarker variance than are exposures and observable covariate effects. The methods described in this analysis should be considered for the selection and interpretation of biomarkers as exposure surrogates in future exposure investigations.     

Least squares estimation and tests of breaks in mean and variance under misspecification

Summary In this paper we investigate the consequences of misspecification on the large sample properties of change‐point estimators and the validity of tests of the null hypothesis of linearity versus the alternative of a structural break. Specifically this paper concentrates on the interaction of structural breaks in the mean and variance of a time series when either of the two is omitted from the estimation and inference procedures. Our analysis considers the case of a break in mean under omitted‐regime‐dependent heteroscedasticity and that of a break in variance under an omitted mean shift. The large and finite sample properties of the resulting least‐squares‐based estimators are investigated and the impact of the two types of misspecification on inferences about the presence or absence of a structural break subsequently analysed.     

A random sampling approach for robust estimation of tissue-to-plasma ratio from extremely sparse data

This study was performed to develop a new nonparametric approach for the estimation of robust tissue-to-plasma ratio from extremely sparsely sampled paired data (ie, one sample each from plasma and tissue per subject). Tissue-to-plasma ratio was estimated from paired/unpaired experimental data using independent time points approach, area under the curve (AUC) values calculated with the naive data averaging approach, and AUC values calculated using sampling based approaches (eg, the pseudoprofile-based bootstrap [PpbB] approach and the random sampling approach [our proposed approach]). The random sampling approach involves the use of a 2-phase algorithm. The convergence of the sampling/resampling approaches was investigated, as well as the robustness of the estimates produced by different approaches. To evaluate the latter, new data sets were generated by introducing outlier(s) into the real data set. One to 2 concentration values were inflated by 10% to 40% from their original values to produce the outliers. Tissue-to-plasma ratios computed using the independent time points approach varied between 0 and 50 across time points. The ratio obtained from AUC values acquired using the naive data averaging approach was not associated with any measure of uncertainty or variability. Calculating the ratio without regard to pairing yielded poorer estimates. The random sampling and pseudoprofile-based bootstrap approaches yielded tissue-to-plasma ratios with uncertainty and variability. However, the random sampling approach, because of the 2-phase nature of its algorithm, yielded more robust estimates and required fewer replications. Therefore, a 2-phase random sampling approach is proposed for the robust estimation of tissue-to-plasma ratio from extremely sparsely sampled data.     

A typological model for estimation of drug and placebo effects in depression

One reason for failure to find specific treatment effects in drug versus placebo trials with patients who have depression is an insufficient period of observation. Also, differentiating between early fleeting response and maintained response has been shown relevant to detecting specific drug action. A model in which various types of drug and placebo response are specifically stipulated and which takes advantage of a two-stage experimental design is proposed.Substantive findings when patients who have major depression with atypical features are studied are: 1) about 6% have only a fleeting response to placebo and no response to drug; 2) by week-10 about 28% of the population will respond even if no medication is given; and 3) specific response to imipramine (21%) can be determined by week-4 but specific response to fluoxetine (20%) cannot be determined until later (week-10 in this study).     

A note on sufficiency in binary panel models

Consider estimating the slope coefficients of a fixed‐effect binary‐choice model from two‐period panel data. Two approaches to semiparametric estimation at the regular parametric rate have been proposed: one is based on a sufficiency requirement, and the other is based on a conditional‐median restriction. We show that, under standard assumptions, both conditions are equivalent.     

A note on the effects of some psychotropic drugs on the aggressive behaviour in the ant, Formica rufa

AGGRESSIVE behaviour in lower animals has not been analysed pharmacologically. Inhibition of the motor activity with simultaneous outbursts of aggressiveness seems to be characteristic in ants treated with reserpine (Kostowski, Beck & Mészáros, 1965; 1966). Among the invertebrates, ants are a suitable subject for studies on aggressiveness because of their tendency to attack other species. We have assessed the influence of drugs on aggressive behaviour in ants and mice.     

A note on concordance correlation coefficient

In this note, we first review some recent developments about measures of agreement, which are often required in medicine and other sciences, with focus on differences between these methods. In the last part, we mention five important concerns when using a newly developed concordance correlation coefficient. Our conclusion is that we need to be especially careful when using existing correlation methods and a new correlation method needs to be developed in the future.