Stratification,Blinding and Placebo Effect in a Randomized,Double Blind Placebo-controlled Clinical Trial of Gold Bead Implantation in Dogs with Hip Dysplasia

The purpose of this study was to investigate the need for and choice of stratification factors, and the effects of blinding and placebo in a clinical experiment. Eighty dogs with canine hip dysplasia (CHD) were included in a randomized, placebo-controlled and double blind clinical trial with stratified parallel group design, in which body weight and degree of CHD were used as stratification factors. Thirty-eight dogs were allocated to gold bead implantation and 42 to placebo. After six months, 33 of the 42 placebo-treated dogs received gold bead implantation in an open study lasting a further 18 months. The main outcome variable in the study was change in pain signs of CHD as assessed by the owner. No significant difference in the main outcome variable, regardless of the treatment given, could be detected in the two chosen stratification factors. The only factor to influence the main outcome variable significantly was age. The blinding procedure used in the study, in which 60% of the owners correctly guessed the treatment given, was found sufficient. Of those who guessed the treatment erroneously, 88% believed the treatment given was gold bead implantation. The treatment efficacy after six months in the blinded treatment group was found to be significantly larger compared to the efficacy obtained in the open study. A significant placebo effect was therefore detected. Conclusion and Clinical Relevance: The age of the dogs influenced the outcome of the CHD treatment, and is recommended as a stratification factor. A significant placebo effect has to be expected and an optimal blinding procedure is necessary in similar clinical studies.     

Incorporating prior parameter uncertainty in the design of sampling schedules for pharmacokinetic parameter estimation experiments

An experiment design procedure is proposed for nonlinear parameter estimation studies that formally incorporates prior parameter uncertainty. The design criterion derives from information theory considerations and involves an asymptotic interpretation of the expected posterior information provided by an experiment. A pharmacokinetic sample schedule design problem is used to illustrate and evaluate this information theoretic design strategy. The model considered is commonly used to describe the plasma concentration of a drug following its oral administration. The limitations and advantages of the proposed design procedure are discussed in relation to other previously reported design techniques for incorporating parameter uncertainty.     

A non-iterative confidence interval estimating procedure for the intraclass kappa statistic with multinomial outcomes

We obtain the asymptotic sample variance of the intraclass kappa statistic for multinomial outcome data. A modified Wald type procedure based on this theory is then used for confidence interval construction. The results of a simulation study show that the proposed non-iterative approach performs very well in terms of confidence interval coverage and width for samples as small as 50. The procedure is illustrated with two examples from previously published medical studies.     

Ultra-high dimensional variable selection for doubly robust causal inference

Causal inference has been increasingly reliant on observational studies with rich covariate information. To build tractable causal procedures, such as the doubly robust estimators, it is imperative to first extract important features from high or even ultra-high dimensional data. In this paper, we propose causal ball screening for confounder selection from modern ultra-high dimensional data sets. Unlike the familiar task of variable selection for prediction modeling, our confounder selection procedure aims to control for confounding while improving efficiency in the resulting causal effect estimate. Previous empirical and theoretical studies suggest excluding causes of the treatment that are not confounders. Motivated by these results, our goal is to keep all the predictors of the outcome in both the propensity score and outcome regression models. A distinctive feature of our proposal is that we use an outcome model-free procedure for propensity score model selection, thereby maintaining double robustness in the resulting causal effect estimator. Our theoretical analyses show that the proposed procedure enjoys a number of properties, including model selection consistency and pointwise normality. Synthetic and real data analysis show that our proposal performs favorably with existing methods in a range of realistic settings. Data used in preparation of this paper were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.     

Inference Procedures for Assessing Interobserver Agreement among Multiple Raters

We propose a new procedure for constructing inferences about a measure of interobserver agreement in studies involving a binary outcome and multiple raters. The proposed procedure, based on a chi-square goodness-of-fit test as applied to the correlated binomial model (Bahadur, 1961, in Studies in Item Analysis and Prediction, 158-176), is an extension of the goodness-of-fit procedure developed by Donner and Eliasziw (1992, Statistics in Medicine 11, 1511-1519) for the case of two raters. The new procedure is shown to provide confidence-interval coverage levels that are close to nominal over a wide range of parameter combinations. The procedure also provides a sample-size formula that may be used to determine the required number of subjects and raters for such studies.     

Incorporating monotonicity into the evaluation of a biomarker

In the assessment of clinical utility of biomarkers, case-control studies are often undertaken based on existing serum samples. A common assumption made in these studies is that higher levels of the biomarker are associated with increased disease risk. In this article, we consider methods of analysis in which monotonicity is incorporated in associating the biomarker and the clinical outcome. We consider the roles of discrimination versus association and assess methods for both goals. In addition, we propose a semiparametric isotonic regression model for binary data and describe a simple estimation procedure as well as attendant inferential procedures. We apply the various methodologies to data from a prostate cancer study involving a serum biomarker.     

A copula approach for detecting prognostic genes associated with survival outcome in microarray studies

A challenging and crucial issue in clinical studies in cancer involving gene microarray experiments is the discovery, among a large number of genes, of a relatively small panel of genes whose elements are associated with a relevant clinical outcome variable such as time-to-death or time-to-recurrence of disease. A semiparametric approach, using dependence functions known as copulas, is considered to quantify and estimate the pairwise association between the outcome and each gene expression. These time-to-event type endpoints are typically subject to censoring as not all events are realized at the time of the analysis. Furthermore, given that the total number of genes is typically large, it is imperative to control a relevant error rate in any gene discovery procedure. The proposed method addresses the two aforementioned issues by direct incorporation of the censoring mechanism and by appropriate statistical adjustment for multiplicity. The performance of the proposed method is studied through simulation and illustrated with an application using a case study in lung cancer.     

An experimental design and a statistical analysis separating interference from exploitation competition

Previous experimental studies of competition among foragers rarely distinguished between exploitation and interference competition. In many systems this separation is experimentally impossible without interfering with the natural behavior of the animals. Consequently, these studies can only demonstrate the combined effect of interference and exploitation on the forager’s feeding rate, namely, it usually decreases in a decelerating rate as a function of density. We suggest here a simple experimental and statistical procedure that facilitates the separation of the effects of interference from those of exploitation. This procedure includes manipulation of both predator density and the foraging experiment duration. The statistical analysis is based on multiple linear regression. The working assumption is that exploitation can be neglected at the beginning of the foraging experiment because, initially, predators do not experience diminishing returns in prey capture rates. Using both the results of an individual-based simulation and a field experiment dataset of gerbils foraging for seeds in an artificial food patch located in the field, we demonstrate that our procedure can successfully detect and separate the effect of interference from the combined overall effect of competition (i.e., interference plus exploitation). Inon Scharf and Ido Filin contributed equally to this paper.     

Analysis of variance tables based on experimental structure

A stepwise procedure for obtaining the experimental structure for a particular experiment is presented together with rules for deriving the analysis-of-variance table from that structure. The procedure involves the division of the factors into groups and is essentially a generalization of the method of Nelder (1965, Proceedings of the Royal Society, Series A 283, 147-162; 1965, Proceedings of the Royal Society, Series A 283, 163-178), to what are termed 'multi-tiered' experiments. The proposed method is illustrated for a wine-tasting experiment.     

A review of psychosocial outcomes for patients seeking cosmetic surgery

The authors reviewed the literature on psychological and psychosocial outcomes for individuals undergoing cosmetic surgery, to address whether elective cosmetic procedures improve psychological well-being and psychosocial functioning and whether there are identifiable predictors of an unsatisfactory psychological outcome. They conducted a search of appropriate computerized databases for studies that evaluated psychological and psychosocial status both before and after elective cosmetic surgery. They identified 37 relevant studies of varying cosmetic procedures that utilized disparate methodologies. Overall, patients appeared generally satisfied with the outcome of their procedures, although some exhibited transient and some exhibited longer-lasting psychological disturbance. Factors associated with poor psychosocial outcome included being young, being male, having unrealistic expectations of the procedure, previous unsatisfactory cosmetic surgery, minimal deformity, motivation based on relationship issues, and a history of depression, anxiety, or personality disorder. Body dysmorphic disorder was also recognized by some studies as a predictor of poor outcome, a finding reinforced by reference to the psychiatric literature. The authors conclude that although most people appear satisfied with the outcome of cosmetic surgical procedures, some are not, and attempts should be made to screen for such individuals in cosmetic surgery settings.     

Methods of adjusted comparison of medians

Consider the problem of making an adjusted comparison of the medians of two populations on an interval type outcome variable. A common method of doing this is through the use of a linear model requiring the residuals to be normally distributed. We describe here two methods based on a linear model after Box–Cox transformation of the outcome variable. The methods require a reference population, which could be either of the populations under study or their aggregate. We compare the new procedures with the comparison of normal means procedure and other procedures proposed for this problem by simulation. It is found that the procedure based on comparison of the predicted values obtained from the observed covariates of the reference population has higher power for testing and smaller mean square error of estimation than the other methods, while maintaining reasonable control of the type I error rate. We illustrate the methods by analyzing the duration of the second stage of labor for women in two large observation studies (Collaborative Perinatal Project and Consortium on Safe Labor) separated by 50 years. We recommend the method based on comparison of the predicted values of the transformed outcomes, with careful attention to how close the resulting residual distribution is to normal.     

Model based design of a biochemical cultivation process

In this paper a simple design procedure is used to enhance the performance of a biotechnical cultivation process. A model supported approach is proposed. It starts with a simple classical process model obtained from literature data, which is used to design the first experiment. Then, the main procedure is an iteration of (i) improving the model making use of the deviations between the experimental data and the data predicted by the model, (ii) of designing the next experiment by determining the optimal control profiles from the current model, and (iii) of executing that designed experiment. Important for the success of the procedure is that the model development is oriented at the process performance. The procedure is demonstrated at the simple practical example of a laboratory-scale fed-batch cultivation of Escherichia coli.     

Automatic procedure for using models of proteins in molecular replacement

In a crystallography experiment, a crystal is irradiated with X-rays whose diffracted waves are collected and measured. The reconstruction of the structure of the molecule in the crystal requires knowledge of the phase of the diffracted waves, information that is lost in the passage from the three-dimensional structure of the molecule to its diffraction pattern. It can be recovered using experimental methods such as heavy-atom isomorphous replacement and anomalous scattering or by molecular replacement, which relies on the availability of an atomic model of the target structure. This can be the structure of the target protein itself, if a previous structure determination is available, or a computational model or, in some cases, the structure of a homologous protein. It is not straightforward to predict beforehand whether or not a computational model will work in a molecular replacement experiment, although some rules of thumb exist. The consensus is that even minor differences in the quality of the model, which are rather difficult to estimate a priori, can have a significant effect on the outcome of the procedure. We describe here a method for quickly assessing whether a protein structure can be solved by molecular replacement. The procedure consists in submitting the sequence of the target protein to a selected list of freely available structure prediction servers, cluster the resulting models, select the representative structures of each cluster and use them as search models in an automatic phasing procedure. We tested the procedure using the structure factors of newly released proteins of known structure downloaded from the Protein Data Bank as soon as they were made available. Using our automatic procedure we were able to obtain an interpretable electron density map in more than half the cases.     

A preliminary study on viral decontamination of chicken serum using gamma-irradiation

A preliminary experiment was carried out to determine whether a decontamination procedure using gamma irradiation, similar to that adopted in the European guideline for bovine serum contaminated by pestivirus, could be applied to chicken serum. Chicken sera spiked with known amounts of enveloped and non-enveloped chicken viruses were gamma irradiated. The remaining live viruses were then measured by titration and the virus reduction capacity of the irradiation process was established for both enveloped and non-enveloped virus models. In parallel with the irradiation procedure, a classical in vivo extraneous agent test was also evaluated in order to see if it has the capacity to detect low enough levels of live viruses to be used for testing irradiated serum. The results suggest that the principles of the bovine serum decontamination procedure may be applied to chicken serum. Further studies are required to determine if this process would provide an acceptable solution for the viral ‘decontamination’ of chicken serum.     

The Heterogeneity in Retrieved Relations between the Personality Trait ‘Harm Avoidance’ and Gray Matter Volumes Due to Variations in the VBM and ROI Labeling Processing Settings

Concerns are raising about the large variability in reported correlations between gray matter morphology and affective personality traits as ‘Harm Avoidance’ (HA). A recent review study (Mincic 2015) stipulated that this variability could come from methodological differences between studies. In order to achieve more robust results by standardizing the data processing procedure, as a first step, we repeatedly analyzed data from healthy females while changing the processing settings (voxel-based morphology (VBM) or region-of-interest (ROI) labeling, smoothing filter width, nuisance parameters included in the regression model, brain atlas and multiple comparisons correction method). The heterogeneity in the obtained results clearly illustrate the dependency of the study outcome to the opted analysis settings. Based on our results and the existing literature, we recommended the use of VBM over ROI labeling for whole brain analyses with a small or intermediate smoothing filter (5-8mm) and a model variable selection step included in the processing procedure. Additionally, it is recommended that ROI labeling should only be used in combination with a clear hypothesis and that authors are encouraged to report their results uncorrected for multiple comparisons as supplementary material to aid review studies.     

Intracerebral grafting in the dopaminergic system: issues and controversy.

A review of work in the dopaminergic system reveals both progress and controversy. More than 100 papers on intracerebral grafting were published last year. Several groups have published the clinical outcome of fetal substantia nigra implants in Parkinsonian patients and studies suggest that sprouting of dopaminergic fibers in response to grafting procedures ameliorates the behavioral deficits of dopamine-depleted animals. Trophic factors for dopamine neurons have also been identified. In addition, genetically modified cells continue to be developed as an alternative method for delivering molecules to the brain. The speed with which neural grafting has become a therapeutic procedure in Parkinsonian patients continues to stimulate debate.     

The consequences of surrendering a degree of freedom to the participant in a contingency assessment task

Many studies of contingency judgments have used a task in which, on each trial, the participant is free either to respond or not to respond, and an outcome may, or may not, be presented. Typically, the experimenter specifies a nominal value for the contingency between responding and outcome, but the actual values of a variety of variables experienced by a particular participant depend on that participant's frequency of responding. The results of computer simulations of various strategies for implementing the contingency manipulation, and the results of an experiment, indicate that the same nominal contingency value will lead to considerable variability in the actual contingency experienced by participants. Moreover, nominal contingency manipulations are confounded with the probability that the subject experiences an outcome. While researchers might be aware of these issues, not enough attention has been paid to their potential impact.     

Analyses of two-way chronic studies

This paper proposes a method for analyzing tumor data from chronic studies when the experimental design includes combinations of two factors, for example, sex and dose. Both main effects and combined-effect (interaction) hypotheses are considered. A stratified log-rank statistic is presented for tests of no column or row (main) effects. The paper shows that when the numbers of animals in the cells are unequal and disproportional, the null distribution of the unstratified log-rank statistic does not have a chi-square distribution. Two simple models, additive and multiplicative, for representing the combined effect of row and column are considered under the proportional hazards model. A simple conservative statistic is proposed for testing the additivity of the row and column effects. A simulation experiment to examine the behavior of the null distribution of the combined-effect test statistic under the additive model and the power of the test against the multiplicative model is reported. The procedure is illustrated by analyzing mammary tumors induced by 7,12-dimethylbenz[a]anthracene (DMBA) in yellow and agouti F1 female mice from a laboratory experiment.     

Analyzing k (2 x 2) tables under cluster sampling

In many data analytic applications, such as ophthalmologic, longitudinal, or periodontal studies, multiple observations are recorded over several sites (or timepoints) within the same subject, bringing about dependence between measurements. This correlation, in turn, precludes the use of standard statistical methods that assume independence between outcome measurements. For example, the Mantel-Haenszel statistic, used to assess association between a binary outcome and a binary exposure while adjusting for a categorical covariate, does not follow the usual chi-squared distribution under the null hypothesis when there is correlation between observations. A modified Mantel-Haenszel procedure, which makes adjustment for dependence, is proposed. No particular correlation structure is assumed for responses within a cluster. This closed-form adjustment stems from Liang and Zeger's (1986, Biometrika 73, 13-22) generalized estimating equations approach for clustered data. The difference between this tabular (i.e., noniterative) technique and many earlier tabular methods is that the current method allows for consideration of site-specific exposure and covariate information. An example from a periodontal research study illustrates application of the method.     

Design and analysis of multiple-choice feeding-preference experiments

Summary A serious omission in ecological methodology is the absence of a rigorous statistical procedure to analyse multiple-choice feeding-preference experiments. A sample of 21 studies in the littoral marine context shows that results from such experiments are used to study a variety of conceptual issues, ranging from nutritional biology to ecosystem dynamics. A majority of such studies have been incorrectly analysed. The analytical problem has two facets: (1) lack of independence in the simultaneous offer of food types and (2) the existence of autogenic changes particular to each food type. Problem (2) requires the use of control arenas without the consumer. A recent advance allows the rigorous analysis of experiments with two food types offered simultaneously. Here I propose a method for the multiple-choice case. For the first problem I suggest the use of multivariate statistical analysis, providing both a parametric and a nonparametric procedure. The second problem is solved using basic statistical theory. I analyse data from an experiment with the sea urchin Tetrapygus niger feeding on three species of algae: Ulva nematoidea, Gymnogongrus furcellatus, and Macrocystis pyrifera. The parametric and nonparametric procedures yielded similar results, and showed that when offered the three species of algae T. niger does not feed at random but shows a preference for U. nematoidea. The method requires that the number of replicates in the treatment and control arenas be the same, and greater than the number of food types. The method is useful for other kinds of multiple-choice experiments.