[Use of nonparametric methods for controlling unseen confounding variables in ecological time-series studies].
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Bias↗
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Results for “Statistics, Nonparametric”
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Time-of-day variations of indicators of attention: performance, physiologic parameters, and self-assessment of sleepiness.
BACKGROUND: A study was performed to analyze time-of-day variations of different indicators of attention and their interrelations. METHODS: After a sufficiently long all-night sleep 12 healthy non-sleep-deprived subjects ran through a test battery (Stanford Sleepiness Scale, Visual Analogue Scale, Critical Flicker Fusion Test [CFF], Visualization Test, Number Facility Test, Reaction Time, Pupillometry, and modified Multiple Sleep Latency Test) every 2 hours from 7:00 AM until 11:00 PM. Time-of-day variations were tested nonparametrically with Friedman's test for repeated measurements. Principal component factor analysis (of individually standardized values) was used to identify variable complexes with the same pattern of time-of-day variation. RESULTS: Statistically significant time-of-day variations were found for all variables, except for Fusion Frequency in CFF and Reaction Time. In factor analysis the physiologic parameters (pupillometric variables and sleep latencies) load on one factor, whereas the self-assessment scales, the Visualization Test, Number Faculty Test, and CFF load on the second factor. The variables that load primarily on factor 1 show peak levels of alertness immediately after getting up (at 7:00 AM) and again at 9:00 PM. Those variables that load primarily on factor 2 indicate a peak level of alertness around noon (11:00 AM-3:00 PM). CONCLUSIONS: Different aspects of attention follow different time-of-day variations. It is discussed, that these findings can be attributed to underlying circadian and homeostatic factors.
Adult↗
Genome scanning for linkage: an overview.
Several different methods for linkage analysis are shown to arise from a single likelihood function L for the observed allele-sharing data at multiple markers in a chromosomal region. These include classical parametric lod score methods, nonparametric or "model-free" affected pedigree-member (APM) methods, and the Gaussian process method. Setting the methods in the context of the likelihood function L clarifies their underlying assumptions. A test statistic derived from L, the efficient score statistic, is introduced. It is asymptotically equivalent to the lod score, but it can be easier to compute when the penetrances and frequencies of alleles of the trait gene are not known. APM test statistics and the Gaussian lod score are shown to be special cases of efficient score statistics. This unified framework facilitates exploration of a range of models for the effects of a putative trait-predisposing gene, and it facilitates sensitivity analyses to examine the consequences of model misspecification.
Female↗
Nonparametric willingness-to-pay measures and confidence statements.
Willingness to pay (WTP) for a health care program can be estimated in contingent valuation (CV) studies by a nonparametric approach. The nonparametric approach is free from distributional assumptions, which is a strength compared with parametric regression-based approaches. However, using a nonparametric approach it is not clear how to obtain confidence statements for WTP estimates, for example, when testing hypotheses regarding differences in mean WTP for different subsamples. The authors propose a procedure that allows statistical testing and confidence interval estimation by employing bootstrap techniques. The method is easy to implement and has low computational costs with modern personal computers. The method is applied to data from a CV study where the WTP for hormone replacement therapy was investigated. The mean WTP was estimated for the full sample and separately for women with mild and severe menopausal symptoms. Using the proposed method, the mean WTP was significantly higher in the group with severe symptoms.
Attitude to Health↗
Effects of 4 hand-drying methods for removing bacteria from washed hands: a randomized trial.
OBJECTIVE: To evaluate the effects of 4 different drying methods to remove bacteria from washed hands. SUBJECTS AND METHODS: One hundred adult volunteers participated in this randomized prospective study. All bacterial counts were determined using a modified glove-juice sampling procedure. The difference was determined between the amounts of bacteria on hands artificially contaminated with the bacterium Micrococcus luteus before washing with a nonantibacterial soap and after drying by 4 different methods (cloth towels accessed by a rotary dispenser, paper towels from a stack on the hand-washing sink, warm forced air from a mechanical hand-activated dryer, and spontaneous room air evaporation). The results were analyzed using a nonparametric analysis (the Friedman test). By this method, changes in bacterial colony-forming unit values for each drying method were ranked for each subject. RESULTS: The results for 99 subjects were evaluable. No statistically significant differences were noted in the numbers of colony-forming units for each drying method (P = .72). CONCLUSION: These data demonstrate no statistically significant differences in the efficiency of 4 different hand-drying methods for removing bacteria from washed hands.
Adult↗
Linkage analysis of complex disorders with multiple phenotypic categories: simulation studies and application to bipolar disorder data.
The problem of linkage analysis of disorders with multiple possible phenotypes (diagnostic spectrum) is considered. A modification is proposed to Ott's [1994] method of down-weighting the contribution of broader diagnoses by reducing penetrance ratios for affected cases. A "robust weighting" strategy considers only the robustness of a set of ratios across a range of true genetic models. Practical models for lod-score analysis will typically employ a high penetrance ratio (> 10) for "core" cases, and ratios between 2 and 5 for broader cases. Results suggest that an additive parametric analysis correlates highly with dominant, recessive and nonparametric linkage (NPL) analyses. A weighted, additive model is then applied to a modified NIMH bipolar chromosome 18 data set (Genetic Analysis Workshop 10) and compared with NPL analyses under narrow and broad diagnostic models. The weighted model performed well. The introduction of similar weights into nonparametric analyses may prove more useful.
Bipolar Disorder↗
[I: Box whisker plots--Flexible alternative to "MSE Plots"].
Data description for continuous parameters is sometimes only based on means and standard deviations of measurement series, graphical representation only concentrates on corresponding "MSE plots", which provide means and standard deviations or even only mean squared errors. However, this strategy is only correct for normally distributed data. Outliers may seriously bias mean and standard deviations and may therefore lead to wrong clinical conclusions. The present paper suggests the use of medians and quartiles, which - just like their graphical pendant, the nonparametric "box whisker plot" - can be applied much more flexibly.
Bias↗
Semiparametric estimation of tag loss and reporting rates for tag-recovery experiments using exact time-at-liberty data.
We present a semiparametric likelihood approach to estimating reporting rates and tag-loss rates from the tags returned from capture-recapture studies. Such studies are commonly used to estimate critical population parameters. Tag loss rates are estimated using double-tagged animals, while reporting rates are estimated using information from high-reward tags. A likelihood function is constructed based on the conditional distribution of the type of tag returned (low or high reward, single or double tag), given that a tag has been returned. This involves many sparse 5 x 1 tag-return contingency tables, and choosing a good functional form for the tag loss rate is difficult with such data. We model tag-loss rates using monotone-smoothing splines, and use these nonparametric estimates to diagnose the parametric form of the tag-loss rate. The nonparametric methods can also be used directly to model tag-loss rates.
Animals↗
Nonparametric linkage does not provide strong evidence for linkage to APOE in a large Alzheimer's kindred.
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Alzheimer Disease↗
Marginal structural models as a tool for standardization.
In this article, we show the general relation between standardization methods and marginal structural models. Standardization has been recognized as a method to control confounding and to estimate causal parameters of interest. Because standardization requires stratification by confounders, the sparse-data problem will occur when stratified by many confounders and one then might have an unstable estimator. A new class of causal models called marginal structural models has recently been proposed. In marginal structural models, the parameters are consistently estimated by the inverse-probability-of-treatment weighting method. Marginal structural models give a nonparametric standardization using the total group (exposed and unexposed) as the standard. In epidemiologic analysis, it is also important to know the change in the average risk of the exposed (or the unexposed) subgroup produced by exposure, which corresponds to the exposed (or the unexposed) group as the standard. We propose modifications of the weights in the marginal structural models, which give the nonparametric estimation of standardized parameters. With the proposed weights, we can use the marginal structural models as a useful tool for the nonparametric multivariate standardization.
Antineoplastic Agents, Hormonal↗
Measuring agreement in method comparison studies.
Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie. We describe how graphical methods can be used to investigate the assumptions of the method and we also give confidence intervals. We extend the basic approach to data where there is a relationship between difference and magnitude, both with a simple logarithmic transformation approach and a new, more general, regression approach. We discuss the importance of the repeatability of each method separately and compare an estimate of this to the limits of agreement. We extend the limits of agreement approach to data with repeated measurements, proposing new estimates for equal numbers of replicates by each method on each subject, for unequal numbers of replicates, and for replicated data collected in pairs, where the underlying value of the quantity being measured is changing. Finally, we describe a nonparametric approach to comparing methods.
Clinical Laboratory Techniques↗
Computer program for statistical Mann-Whitney U nonparametric analysis of neuronal spike activity.
A program for neuronal activity analysis is described. The applied computational techniques are standard in the field of digital processing, but the program is particular in its field of application and mode of data selection. The program, written in Turbo Pascal for the IBM-PC and compatibles, statistically compares (Mann-Whitney U-test) two sets of graphically selected data, and establishes whether there are significant differences between them. Although the program was developed for spike frequency analysis, it can easily be adapted to perform statistical analysis of other kinds of data.
Action Potentials↗
A genome-wide scanning and fine mapping study of COGA data.
A thorough genetic mapping study was performed to identify predisposing genes for alcoholism dependence using the Collaborative Study on the Genetics of Alcoholism (COGA) data. The procedure comprised whole-genome linkage and confirmation analyses, single locus and haplotype fine mapping analyses, and gene x environment haplotype regression. Stratified analysis was considered to reduce the ethnic heterogeneity and simultaneously family-based and case-control study designs were applied to detect potential genetic signals. By using different methods and markers, we found high linkage signals at D1S225 (253.7 cM), D1S547 (279.2 cM), D2S1356 (64.6 cM), and D7S2846 (56.8 cM) with nonparametric linkage scores of 3.92, 4.10, 4.44, and 3.55, respectively. We also conducted haplotype and odds ratio analyses, where the response was the dichotomous status of alcohol dependence, explanatory variables were the inferred individual haplotypes and the three statistically significant covariates were age, gender, and max drink (the maximum number of drinks consumed in a 24-hr period). The final model identified important AD-related haplotypes within a candidate region of NRXN1 at 2p21 and a few others in the inter-gene regions. The relative magnitude of risks to the identified risky/protective haplotypes was elucidated.
Alcoholism↗
Mann-Whitney/Wilcoxon's nonparametric cumulative probability distribution.
It is demonstrated how complete nonparametric, cumulative probability distributions for Mann-Whitney/Wilcoxon's nonparametric, two-sample test can be constructed based on algorithms published earlier in this journal. These procedures provide cumulative probabilities for all possible rank sums in the nonparametric two-sample test. Separate programs for MS(PC)-DOS and Macintosh computers are offered.
Algorithms↗
Nonparametric estimation of bounded survival functions with censored observations.
Stochastic ordering of survival functions is a useful concept in many areas of statistics, especially in nonparametric and order restricted inferences. In this paper we introduce an algorithm to compute maximum likelihood estimates of survival functions where both upper and lower bounds are given. The algorithm allows censored survival data. In a simulation study, we found that the proposed estimates are more efficient than the unrestricted Kaplan-Meier product limit estimates both with and without censored observations.
Algorithms↗
Nonparametric estimation of sojourn time distributions for truncated serial event data--a weight-adjusted approach.
In follow-up studies, survival data often include subjects who have had a certain event at recruitment and may potentially experience a series of subsequent events during the follow-up period. This kind of survival data collected under a cross-sectional sampling criterion is called truncated serial event data. The outcome variables of interest in this paper are serial sojourn times between successive events. To analyze the sojourn times in truncated serial event data, we need to confront two potential sampling biases arising simultaneously from a sampling criterion and induced informative censoring. In this study, nonparametric estimation of the joint probability function of serial sojourn times is developed by using inverse probabilities of the truncation and censoring times as weight functions to accommodate these two sampling biases under various situations of truncation and censoring. Relevant statistical properties of the proposed estimators are also discussed. Simulation studies and two real data are presented to illustrate the proposed methods.
Accidents↗
Evaluating markers for selecting a patient's treatment.
Selecting the best treatment for a patient's disease may be facilitated by evaluating clinical characteristics or biomarker measurements at diagnosis. We consider how to evaluate the potential impact of such measurements on treatment selection algorithms. For example, magnetic resonance neurographic imaging is potentially useful for deciding whether a patient should be treated surgically for Carpal Tunnel Syndrome or should receive less-invasive conservative therapy. We propose a graphical display, the selection impact (SI) curve that shows the population response rate as a function of treatment selection criteria based on the marker. The curve can be useful for choosing a treatment policy that incorporates information on the patient's marker value exceeding a threshold. The SI curve can be estimated using data from a comparative randomized trial conducted in the population as long as treatment assignment in the trial is independent of the predictive marker. Estimating the SI curve is therefore part of a post hoc analysis to determine whether the marker identifies patients that are more likely to benefit from one treatment over another. Nonparametric and parametric estimates of the SI curve are proposed in this article. Asymptotic distribution theory is used to evaluate the relative efficiencies of the estimators. Simulation studies show that inference is straightforward with realistic sample sizes. We illustrate the SI curve and statistical inference for it with data motivated by an ongoing trial of surgery versus conservative therapy for Carpal Tunnel Syndrome.
Algorithms↗
Registration of births, stillbirths and infant deaths in Jamaica.
BACKGROUND: Vital statistics underestimate the prevalence of perinatal and infant deaths. This is particularly significant when these parameters affect eligibility for international assistance for newly emerging nations. OBJECTIVE: To determine the level of registration of livebirths, stillbirths and infant deaths in Jamaica. METHODOLOGY: Births, stillbirths and neonatal deaths identified during a cross-sectional study (1986); and infant deaths identified in six parishes (1993) were matched to vital registration documents filed with the Registrar General. RESULTS: While 94% of livebirths were registered by one year of age (1986), only 13% of stillbirths (1986) and 25% of infant deaths (1993) were registered. Post neonatal deaths were more likely to be registered than early neonatal deaths. Frequently the birth was not registered when the infant died. Birth registration rates were highest in parishes with high rates of hospital deliveries (rs = 0.97, P < 0.001) where institutions notify the registrar of each birth. Hospital deaths, however, were less likely to be registered than community deaths as registrars are not automatically notified of these deaths. CONCLUSIONS: To improve vital registration, institutions should become registration centres for all vital events occurring there (births, stillbirths, deaths). Recommendations aimed at modernizing the vital registration system in Jamaica and other developing countries are also made.
Birth Certificates↗