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PubMed1992

A bootstrap resampling procedure for model building: application to the Cox regression model.

A common problem in the statistical analysis of clinical studies is the selection of those variables in the framework of a regression model which might influence the outcome variable. Stepwise methods have been available for a long time, but as with many other possible strategies, there is a lot of criticism of their use. Investigations of the stability of a selected model are often called for, but usually are not carried out in a systematic way. Since analytical approaches are extremely difficult, data-dependent methods might be an useful alternative. Based on a bootstrap resampling procedure, Chen and George investigated the stability of a stepwise selection procedure in the framework of the Cox proportional hazard regression model. We extend their proposal and develop a bootstrap-model selection procedure, combining the bootstrap method with existing selection techniques such as stepwise methods. We illustrate the proposed strategy in the process of model building by using data from two cancer clinical trials featuring two different situations commonly arising in clinical research. In a brain tumour study the adjustment for covariates in an overall treatment comparison is of primary interest calling for the selection of even 'mild' effects. In a prostate cancer study we concentrate on the analysis of treatment-covariate interactions demanding that only 'strong' effects should be selected. Both variants of the strategy will be demonstrated analysing the clinical trials with a Cox model, but they can be applied in other types of regression with obvious and straightforward modifications.

Brain Neoplasms↗
PubMed1991

An approach to select the appropriate statistical method for testing bioequivalence.

Since most bioavailability studies are usually done with only a limited number of volunteers (usually 10-30), the statistical properties of the calculated bioavailability parameters are not well defined. The established statistical methods to test bioequivalence are usually based on either the assumption of normality or a symmetrical distribution. However, the decision of which method to apply, depends primarily on the distributional assumption of the data. In this study, an approach is followed where the small data base of a limited number of volunteers is expanded by adding pseudo-volunteers by "bootstrap" simulations. From such a larger data base it is easier to determine the statistical distributional properties of bioavailability parameters, which in its turn leads to the identification of an appropriate statistical method. With more certainty on which statistical method to apply, the original data can be used more effectively in testing for bioequivalence. In this paper, comparisons are made between the distributions of bioavailability parameters of an actual 60-volunteer study and those of two simulated data sets. Each such data set contained a random sample of 10 volunteers each (from the 60 volunteers), together with 50 pseudo-volunteers. These 50 volunteers were simulated from the random sample of 10 real volunteers. Good correspondences were obtained when comparing these two data sets with the original data, which indicated the validity to use this approach in bioavailability studies where a small number of volunteers had been used. This method proved useful to define the distributional properties for a relative small number of parameter-values available.

Biological Availability↗
PubMed1990

DNA/DNA hybridization studies of the carnivorous marsupials. I: The intergeneric relationships of bandicoots (Marsupialia: Perameloidea).

A complete suite of comparisons among six bandicoot species and one outgroup marsupial was generated using the hydroxyapatite chromatography method of DNA/DNA hybridization; heterologous comparisons were also made with three other bandicoot taxa. Matrices of delta Tm's, delta modes, and delta T50Hs were generated and corrected for nonreciprocity, homoplasy, and, in the case of delta Tm's, normalized percent hybridization; these matrices were analyzed using the FITCH algorithm in Felsenstein's PHYLIP (version 3.1). Uncorrected and nonreciprocity-corrected matrices were also jackknifed and analyzed with FITCH to test for consistency. Finally, sample scores for delta Tm, delta mode, and delta T50H matrices were bootstrapped and then subjected to phylogenetic analysis. These manipulations were carried out, in part, to address criticisms of the statistics used to summarize DNA/DNA hybridization (especially T50H) and the method itself. However, with the exception of an unresolved trichotomy among the two Echymipera species and Peroryctes longicauda, all trees showed the same branchpoints. Except in the case of the tree generated from reciprocal-corrected delta Tm data, nodes were stable under jackknifing; and, again excepting the above-mentioned trichotomy, all nodes were supported by 95% or more of the bootstrapped trees. These results suggest that, despite arguments to the contrary, all three summary statistics can be valid for DNA/DNA hybridization data. Of taxonomic interest is the placement of Echymipera spp. and Peroryctes longicauda together and separate from the more distant Peroryctes raffrayanus; the genus Peroryctes is thus at least paraphyletic. The trees further grouped Echymipera-plus-Peroryctes as the sister group of Isoodon-plus-Perameles. Limited hybridizations with Macrotis lagotis suggest that its current position as representative of an entirely distinct family of perameloids is correct.

Animals↗
PubMed1992

[Jackknife and bootstrap].

The jackknife and the bootstrap are two non parametric methods which provide estimates- of the bias and the variance of an estimator, without any assumption about its statistical distribution. The jackknife is based on the observation of the estimator for subsamples, generally of size n-1, obtained from the original sample. The bootstrap is based on the observation of the estimator on size n samples drawn from the original sample. The two methods are presented, their principle is illustrated through their application to simple examples and to more complex epidemiological problems.

Bias↗
PubMed1989

Using permutation tests and bootstrap confidence limits to analyze repeated events data from clinical trials.

In clinical trials comparing treatments for superficial bladder cancer, patients are at risk of repeated recurrences of their disease. Statistical methods of analyzing such data are required. This article presents a nonparametric approach. A statistical test to compare the recurrence or tumor rates in two treatment groups, using the randomization distribution, is described. Confidence intervals for the rate ratio are determined from the bootstrap distribution. The implementation of both requires Monte Carlo methods. Computer simulations support the use of these nonparametric methods when there are more than 60 recurrences in each treatment group. An example illustrating their use is given. The strategy adopted for analysis of these data could be applied to other clinical trials where standard methodology is inappropriate.

Biometry↗
PubMed1985

Comparison of receiver operating curves derived from the same population: a bootstrapping approach.

The receiver operating curve (ROC) gives a representation of sensitivity and specificity of a prediction model when varying the cutpoint of a decision rule on a whole spectrum. Evaluation of two models established (or tested) in the same population of patients warrants a valid statistical comparison of their ROC curves. Hanley et al. recently provided a method for overall comparison of ROC curves (J. A. Hanley and B. J. McNeil, Radiology 148, 839-843, 1983). Often ROC curves cross, or differ in only a part of their courses. Bootstrapping of ROC curves is proposed as a graphical check for the statistical significance of differences confined to a part of the curve. An example comparing two models of prediction of coronary artery disease progression is given to illustrate this new approach.

Coronary Angiography↗
PubMed1987

Adjusting for confounded variables: pulmonary function and smoking in a special population.

Confounded variables present an obstacle to valid inference in many environmental and occupational studies. We describe a series of procedures that we used to address this problem in a study of pulmonary function and smoking. Subjects were drawn from the Multiple Risk Factor Intervention Trial (MRFIT), a prospective study of coronary heart disease. Confounding of smoking, hypertension, and hyperlipidemia was designed into the trial and was beyond the control of our ancillary study. We used statistical techniques to detect and characterize the pattern of confounding, identify important variables affecting pulmonary function, and perform appropriate adjustments for extraneous influences (i.e., other than smoking). Among the techniques we used were factor analysis, stepwise multiple regression, and bootstrap replication. Analysis of the adjusted pulmonary function measurements showed that they were satisfactorily standardized and free of artifact. Moreover, use of the adjusted values sharpened our statistical results concerning smoking, the ultimate object of the study. We contrast the use of external and internal standards and discuss methods for detecting, ruling out, or counteracting confounding.

Adult↗
PubMed1991

A statistical method for assessing a threshold in epidemiological studies.

I describe a method for estimating and testing a threshold value in epidemiological studies. A threshold effect indicates an association between a risk factor and a defined outcome above the threshold value but none below it. An important field of application is occupational medicine where, for a lot of chemical compounds and other agents which are non-carcinogenic health hazards, so-called threshold limit values or TLVs are specified. The method is presented within the framework of the logistic regression model, which is widely used in the analysis of the relationship between some explanatory variables and a dependent dichotomous outcome. In most available programs for this and also for other models the concept of a threshold is disregarded. The method for assessing a threshold consists of an estimation procedure using the maximum-likelihood technique and a test procedure based on the likelihood-ratio statistic R, following under the null hypothesis (no threshold) a quasi one-sided chi 2 distribution with one degree of freedom. This use of this distribution is supported by a simulation study. The method is applied to data from an epidemiological study of the relationship between occupational dust exposure and chronic bronchitic reactions. The results are confirmed by bootstrap resampling.

Bronchitis↗
PubMed1986

An approach to quantification of biaxial tissue stress-strain data.

Delineation of the mechanical properties of biologic tissues is one of the cornerstones of biomechanics. Abundant data from uniaxial tests exist but these cannot be extrapolated to describe three-dimensional properties of tissue. Biaxial stress-strain studies have been performed using skin, blood vessels and pericardium. Quantitative description of tissue properties in these studies has employed either polynomial or exponential strain-energy functions. Interpretation of these data, however, is difficult because of wide variability of the estimated coefficients of these functions. This variability has been attributed to experimental noise, numerical instabilities in the algorithms, or to strain-history dependence. No systematic method has been proposed to evaluate the variability. This paper describes a statistically based approach to assessing the sources of and accounting for variability of coefficients in describing biaxial stress-strain data. Our data are from canine pericardium subjected to various combinations of simultaneous biaxial stretching. We first determine a suitable strain-energy function with the least number of free parameters that will fit the data reasonably. We then perform residual analysis to see if standard statistical methods can be used to assess the variability. If not, we use a nonparametric method called bootstrapping that is suitable for assessing the uncertainty in the coefficients. Using a five-parameter exponential strain-energy function, pericardial tissue is found to be strain-history dependent and anisotropic. These findings cannot be attributed to either experimental noise or instability in the numerical algorithms.

Animals↗
PubMed1992

MacT: Apple Macintosh programs for constructing phylogenetic trees.

MacT is a set of programs for the Apple Macintosh to construct and evaluate unrooted trees derived from amino acid sequences using a distance matrix method. Programs are designed on a 'one program--one task' basis for (i) determining the branching order in trees consisting of four or five species and calculating various statistical measures, (ii) calculating statistical measures for all possible topologies of unrooted trees and (iii) generating and evaluating trees derived from bootstrapped samples. With four auxiliary programs unrooted trees can be built for maximal 26 species, and the robustness of topologies be tested by bootstrapping.

Algorithms↗
PubMed1988

Analysis of the time distribution and time sequence of behavioral acts.

A technique for analyzing the temporal structure between various initiations of a particular behavioral act has been developed using a parameter known as the K-function, the cornerstone of recent statistical research on spatial point processes and patterns. The technique has been extended to the study of the joint relationship of separate acts. Bootstrap methods are used to estimate the uncertainty in these measures. The usefulness of these techniques is demonstrated using data from studies of rats exposed to phenytoin and nitrous oxide.

Animals↗
PubMed1992

Comparison of 5.8S ribosomal DNA sequences among the basidiomycetous yeast genera Cystofilobasidium, Filobasidium and Filobasidiella.

Nucleotide sequences obtained from regions of the ribosomal DNA repeat were compared by phylogenetic methods and combined with a statistical evaluation to clarify the relationships among the genera Cystofilobasidium, Filobasidium (F.) and Filobasidiella (Fl.), to assess the affinity of Filobasidiella neoformans and Filobasidiella depauperata, and to compare the varieties of Fl. neoformans. With appropriate primers, the nuclear 18S, 5.8S and internal transcribed spacer (ITS) regions of the ribosomal RNA genes (rDNA) of 10 strains were amplified with the polymerase chain reaction. The resulting DNA products were compared by digestion with endonucleases and analysis of restriction fragments. Single strands of the 5.8S rDNA and ITS regions were subsequently sequenced by the dideoxy method. Statistical support for the phylogeny inferred from parsimony analysis of aligned 5.8S rDNA sequences was determined by bootstrapping. There were no nucleotide substitutions in this region, nor in the ITS, among strains of Fl. neoformans that differ in variety and serotype. There was strong support for retaining Fl. depauperata and Fl. neoformans in the same genus, but nucleotide substitutions can be used to distinguish the two species. There was no support for combining the genera Filobasidium, Filobasidiella or Cystofilobasidium.

Base Sequence↗
PubMed2026

Associations of Illness Perception, Resignation Coping, and Social Support With Self-Regulatory Fatigue in Patients With Type 2 Diabetes: A Cross-Sectional Study.

AIMS: To examine the associations among illness perception, resignation coping, social support, and self-regulatory fatigue (SRF) in patients with Type 2 diabetes mellitus. The study specifically explores whether resignation coping and social support exhibit indirect associations with SRF in the context of illness perception. DESIGN: A cross-sectional study. METHODS: From November 2024 to October 2025, a convenience sample of 302 adult patients with T2DM was recruited from a tertiary general hospital in China. Participants completed validated instruments with established psychometric properties, namely the Brief Illness Perception Questionnaire, the Medical Coping Modes Questionnaire, the Perceived Social Support Scale, and the Self-Regulatory Fatigue Scale. Statistical analyses included Spearman correlation and serial mediation analysis using the PROCESS Macro (Model 6) with bias-corrected bootstrapping. RESULTS: SRF was positively correlated with negative illness perception (r&#x2009;=&#x2009;0.579, p&#x2009;<&#x2009;0.01) and resignation coping (r&#x2009;=&#x2009;0.612, p&#x2009;<&#x2009;0.01), and negatively correlated with social support (r&#x2009;=&#x2009;-0.598, p&#x2009;<&#x2009;0.01). Serial mediation analysis revealed that illness perception was associated with SRF through indirect pathways involving resignation coping and social support. Resignation coping and social support mediated the association between illness perception and self-regulatory fatigue, both individually and sequentially. CONCLUSIONS: Negative illness perception correlates with higher SRF. This observed correlation is additionally linked to indirect pathways involving resignation coping and lower social support. Collectively, these findings highlight a pattern of interrelated cognitive (illness perception), behavioural (resignation coping), and resource (social support) factors that are associated with self-regulatory fatigue in this cross-sectional study. IMPLICATIONS FOR THE PROFESSION: The findings offer a clear, evidence-based framework for nursing practice. They highlight the potential value of integrated assessment and intervention that simultaneously addresses patients' illness beliefs, maladaptive coping strategies, and social support systems, which are associated with lower SRF and better diabetes self-management. REPORTING METHOD: This study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies. PATIENT OR PUBLIC CONTRIBUTION: Patients participated solely as research participants by providing survey data. They were not involved in the study design, implementation, data analysis, interpretation, or manuscript preparation. All patients provided written informed consent prior to questionnaire completion.

Humans↗
PubMed1987

Bootstrapped potential circadian harbingers if not determinants of cardiovascular risk.

Among 12 endocrine variables in blood from clinically healthy adult women sampled systematically around the clock and the year, discriminant analysis methods have singled out certain hormones in certain seasons as classifiers for a high or low risk of developing diseases associated with a high circadian rhythm-adjusted mean (midline estimating statistic of rhythm, MESOR, M) of blood pressure, i.e., risk of M-hypertension (RMH). Before extending the labor intensive, costly data base, showing circadian changes with RMH, we reanalyzed available data by circadian bootstrapping, complementing earlier circannual bootstrapping. Differences in circadian M for aldosterone in all four seasons and for TSH in spring and summer (the only seasons checked), but not for the cortisol M checked in spring and summer, are validated, as are differences in circadian amplitude for TSH in spring and summer and aldosterone in spring. Identification of classifiers provides cost-effective, time-specified endocrine checks complementing the targeted automatic monitoring of blood pressure as part of a system of chronobioengineering for health maintenance.

Adolescent↗
PubMed1988

Estimating the power of the two-sample Wilcoxon test for location shift.

Traditional methods for calculating the power of a statistical test for location shift require knowledge of the shape of the underlying probability distribution. The distribution shape, however, may be unknown. This paper describes a bootstrap method for using observed data (or pilot data) to approximate the power. No assumptions need be made about the shape of the underlying continuous probability distribution. Simulation evidence shows that, when applied to the Wilcoxon two-sample test for location shift, the suggested method is reliable. The evidence also shows that it is more accurate than a benchmark traditional approach. The bootstrap method is applied to a real-data example. The analysis demonstrates how the method can be used to determine sample sizes and how to choose the more powerful of two alternative tests for location shift.

Animals↗
PubMedDate not supplied

The use of GLIM and the bootstrap in assessing a clinical trial of two drugs.

An approach is described for estimating the dose of a new drug which is equipotent to an established dose of an old drug. The approach is basically that of the parallel-line assay but it can allow for concomitant variables and, by exploiting the facilities available in the statistical computer package GLIM (generalized linear interactive modelling), the approach can be applied when the residuals conform to one of a number of distributions and, with suitable safeguards, to continuous, discrete and even 'scored' responses. In some circumstances, it is necessary to obtain confidence limits by Efron's 'bootstrap' technique. The method is illustrated with results from a trial of two premedicant drugs in children.

Biometry↗