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PubMed2000

Bias and prevalence effects on kappa viewed in terms of sensitivity and specificity.

Paradoxical effects of bias and prevalence on the kappa coefficient are examined using the concepts of sensitivity and specificity. Results that appear paradoxical when viewed as a 2 x 2 table of frequencies do not appear paradoxical when viewed as a pair of sensitivity and specificity measures where each observer is treated as a predictor of the other observer. An adjusted kappa value can be obtained from these sensitivity/specificity measures but simulation studies indicate that it would result in substantial overestimation of reliability when bias or prevalence effects are observed. It is suggested that investigators concentrate on obtaining populations with trait prevalence near 50% rather than searching for statistical indices to rescue or excuse inefficient experiments.

Bias↗
PubMed2006

Omnibus permutation tests of the overall null hypothesis in datasets with many covariates.

Tests of the overall null hypothesis in datasets with one outcome variable and many covariates can be based on various methods to combine the p-values for univariate tests of association of each covariate with the outcome. The overall p-value is computed by permuting the outcome variable. We discuss the situations in which this approach is useful and provide several examples. We use simulations to investigate seven omnibus test statistics and find that the Anderson-Darling and Fisher's statistics are superior to the others.

Computer Simulation↗
PubMed2005

SDMinP: a program to control the family wise error rate using step-down minP adjusted P-values.

SDMinP is an easy-to-use program for fast calculation of empirical and adjusted P-values for correlated and uncorrelated hypotheses in multiple testing experiments. It is based on the Free Step-Down Resampling Method for controlling the family wise error rate, and implements a variation of an efficient algorithm, which reduces the originally required re-sampling effort considerably and makes the method computationally feasible. The program is independent of the underlying test statistic and works with provided observed and permutation test statistics.

Algorithms↗
PubMed2003

Mapping quantitative trait loci using multiple phenotypes in general pedigrees.

The use of correlated phenotypes may dramatically increase the power to detect the underlying quantitative trait loci (QTLs). Current approaches for multiple phenotypes include regression-based methods, the multivariate variance of components method, factor analysis and structural equations. Issues with these methods include: 1) They are computation intensive and are subject to problems of optimization algorithms; 2) Existing claims on the asymptotic distribution of the likelihood ratio statistic for the multivariate variance of components method are contradictory and erroneous; 3) The dimension reduction of the parameter space under the null hypothesis, a phenomenon that is unique to multivariate analyses, makes the asymptotic distribution of the likelihood ratio statistic more complicated than expected. In this article, three cases of varying complexity are considered. For each case, the efficient score statistic, which is asympotically equivalent to the likelihood ratio statistic, is derived, so is its asymptotic distribution [correction]. These methods are straightforward to calculate. Finite-sample properties of these score statistics are studied through extensive simulations. These score statistics are for use with general pedigrees.

Algorithms↗
PubMed2006

Statistical treatment of exacerbations in therapeutic trials of chronic obstructive pulmonary disease.

Randomized trials and a meta-analysis suggesting that inhaled corticosteroids reduce exacerbation rates in patients with chronic obstructive pulmonary disease (COPD) show major discrepancies that may be due to different approaches to data analysis. These trials used statistical techniques that were either weighted or unweighted for follow-up time, with p values and confidence intervals estimated with or without accounting for between-patient variability in exacerbation rates. We illustrate the validity of these methods using data from a cohort of 5,454 patients with COPD structured to emulate a randomized trial. The "reference" group was defined as patients with a history of exacerbations before cohort entry (n=1,137), whereas the "treated" group included an equal number (n=1,137) of patients with no prior exacerbation. Random samples of 100 and 200 subjects were selected three times from each of two groups to further illustrate the variability in the findings. Exacerbations during follow-up were identified from prescriptions for systemic antibiotics. The correct rate ratio of 0.75 estimated by the weighted approach was underestimated as 0.57 by the unweighted approach. When the weighted approach did not, however, also account for between-patient variability, the p value was greatly underestimated (e.g., rate ratio, 0.79; p=0.0007 instead of p=0.12) and confidence intervals were much narrower than after properly accounting for this variability. In conclusion, the reports from randomized trials and the meta-analysis that inhaled corticosteroids reduce COPD exacerbation rates are the result of improper statistical analysis techniques. The only two studies that used the correct statistical approach found insignificant effects with these drugs.

Clinical Trials as Topic↗
PubMed2001

Missing predictors in models of effect size.

Missing data occur frequently in meta-analysis. Reviewers inevitably face decisions about how to handle missing data, especially when predictors in a model of effect size are missing from some of the identified studies. Commonly used methods for missing data such as complete case analysis and mean substitution often yield biased estimates. This article briefly reviews the particular problems missing predictors cause in a meta-analysis, discusses the properties of commonly used missing data methods, and provides suggestions for ways to handle missing predictors when estimating effect size models. Maximum likelihood methods for multivariate normal data and multiple imputation hold the most promise for handling missing predictors in meta-analysis. These two model-based methods apply to a broad set of data situations, are based on sound statistical theory, and utilize all information available to obtain efficient estimators.

Data Interpretation, Statistical↗
PubMedDate not supplied

Power and sample size in cost-effectiveness analysis.

For resource allocation under a constrained budget, optimal decision rules for mutually exclusive programs require that the treatment with the highest incremental cost-effectiveness ratio (ICER) below a willingness-to-pay (WTP) criterion be funded. This is equivalent to determining the treatment with the smallest net health cost. The designer of a cost-effectiveness study needs to select a sample size so that the power to reject the null hypothesis, the equality of the net health costs of two treatments, is high. A recently published formula derived under normal distribution theory overstates sample-size requirements. Using net health costs, the authors present simple methods for power analysis based on conventional normal and on nonparametric statistical theory.

Bias↗
PubMed2000

Psychology without p values. Data analysis at the turn of the 19th century.

Although the fledgling psychology of 100 years ago was assertively empirical, there were no inferential statistics to guide psychologists' data analyses. However, 19th-century developments had left psychology with a rich array of techniques for analyzing and presenting data, some of which remain underutilized today. These include comparisons across replications, within-subject designs, reanalysis of data, analyses of factorial designs, and especially the use of tables and graphs. As the merits of hypothesis-testing statistics are debated at the turn of the 21st century, the history of data-handling practices can remind psychologists that there are many ways to overcome the current uniformity of statistical practice.

Data Interpretation, Statistical↗
PubMed2002

[Efficiency of rehabilitation methods in the treatment of arm lymphedema after breast cancer surgery].

In this article we analyze influence of rehabilitation methods in treatment of arm lymphedema. In Kaunas oncological hospital were examined 60 women after surgery for breast cancer. The work objective was to evaluate efficiency of rehabilitation methods in treatment of arm lymphedema and in evaluate movement amplitude of shoulder joint. Two groups of women depending on rehabilitation start were evaluated. The same methods of rehabilitation were applied to both groups: physical therapy, electrostimulation, massage, lymphodrainage with apparate. Our study indicated that women, who were treated at early period of rehabilitation (3 months), showed statistically significantly (p < 0.01) better results in increase of movement amplitude of shoulder joint. However, results of treatment of arm lymphedema, comparing with women who started rehabilitation after 12 months, were equally successful--results were not statistically significantly better (p > 0.05).

Arm↗
PubMed2004

[Evaluation of combined menisci repair results].

Between 2001 and 2003 sixteen patients underwent repair of the menisci with combined "outside-inside", "all-inside" and reabsorbable arrow techniques. This prospective study compared two patient groups: combined fixation group (16 patients) and "outside-inside" fixation group (16 patients). Patients were evaluated using Lysholm and Tegner activity scales. Results of 12 (87.5%) patients in combined fixation group were excellent and good at the time of last follow-up. Results of 10 (62.5%) patients in "outside-inside" fixation group were excellent and good 10 months post operations. There was statistically significant difference between the groups (p<0.05).

Arthroscopy↗
PubMed2005

[Quality control of Corydalis Yanhusuo W. T. Wang by second derivative FTIR spectroscopy combined with statistics].

A new method using single reflection Fourier transform infrared spectroscopy was proposed for direct and fast determination of Corydalis yanhusuo W. T. Wang of traditional Chinese herbal medicines and its confusable varieties. Data were collected directly for Fourier transform infrared spectra with OMNI sampler. Then through converting FTIR spectra of the samples into second derivative spectra by derivative spectra software, it is possible to identify Corydalis yanhusuo W. T. Wang from the confusable varieties with statistics. The result shows that the second derivative FTIR of Corydalis yanhusuo W. T. Wang and its confusable varieties are different in the 2 050-650 cm(-1) range. The probability is less than 0.01 and the result is significant. Corydalis yanhnsuo W. T. Wang and its confusable varieties can be identified by identifying the inner layer parts of the cuticles of samples by second derivative FTIR spectroscopy with statistics directly, rapidly and accurately.

Corydalis↗
PubMed2005

Syndromic surveillance on the epidemiologist's desktop: making sense of much data.

INTRODUCTION: Syndromic surveillance systems are becoming increasingly common in health departments. These systems represent a substantial improvement in the timeliness of ascertainment of community health status. For the value of such systems to be realized, protocols are needed for review and analysis of the findings that these systems produce. METHODS: A workgroup of experienced syndromic surveillance users and developers was convened to discuss approaches to data review and analyses. The discussion was structured to include general principles of the use of syndromic surveillance; how and why specific data are reviewed; integration of multiple data sources; daily versus research uses of systems; how data anomalies are identified by users and surveillance systems; the relative merits of anomalies; how a data anomaly is investigated to determine if it warrants a public health response; and how such a public health response should be framed. RESULTS: From this discussion, a generalized and more detailed process was documented that describes the common elements of analysis used by the workgroup participants. CONCLUSION: Establishment of a framework for evaluation and response to syndromic surveillance data will facilitate the implementation of these systems and standardization of procedures for validation of system findings. Careful development of an evaluation and response framework should be undertaken to assess whether use of syndromic surveillance systems requires excess work to distinguish between statistical anomalies and important public health events.

Data Interpretation, Statistical↗
PubMed1991

The role of depressive disorder in the suicidal behavior of alcoholics.

In order to examine the role depressive disorders play in the genesis of suicidal behavior of alcoholics, 330 alcoholic inpatients were examined. Within the total sample, 41% had distinct suicidal tendencies, and of those, 15% had made at least one serious suicide attempt. The MADRS and MMPI scales were used to obtain objective evaluation of the depressive disorders. The subjects were classified according to DSM-R criteria. The results show that suicidal alcoholics have statistically significantly more depressive characteristics.

Alcoholism↗
PubMed1995

Basic statistics for clinicians: 4. Correlation and regression.

Correlation and regression help us to understand the relation between variables and to predict patients' status in regard to a particular variable of interest. Correlation examines the strength of the relation between two variables, neither of which is considered the variable one is trying to predict (the target variable). Regression analysis examines the ability of one or more factors, called independent variables, to predict a patient's status in regard to the target or dependent variable. Independent and dependent variables may be continuous (taking a wide range of values) or binary (dichotomous, yielding yes-or-no results). Regression models can be used to construct clinical prediction rules that help to guide clinical decisions. In considering regression and correlation, clinicians should pay more attention to the magnitude of the correlation or the predictive power of the regression than to whether the relation is statistically significant.

Data Interpretation, Statistical↗
PubMed1996

[Genes of human viruses are less redundant than human genes].

Statistical parameters of nucleotide sequences of mature human RNAs and those of human viruses were compared. The redundancy values of the appropriate genes were compared. The redundancy of virus genes was shown to be, on the average, less than that of human genes. The distribution of human genes according to redundancy values is bimodal, and that of human virus genes is trimodal. This fact suggests possibility of a novel gene classification according to statistical characteristics of nucleotide sequences.

Data Interpretation, Statistical↗
PubMed1999

[Polysomnographic screening of infants at risk for SIDS].

The authors present a Sudden Infant Death Syndrome prevention program. The study analyses the data of 92 children having participated in the complex prevention program, including polysomnography, between May 1997 and February 1998. The role of polysomnography and its use as a clinical method is described through the statistical analysis of the results of the study.

Data Interpretation, Statistical↗