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Results for “statistical inference”

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At least 19 recordsLinked to original sources
PubMed1988

Statistical inference from single channel records: two-state Markov model with limited time resolution.

Though stochastic models are widely used to describe single ion channel behaviour, statistical inference based on them has received little consideration. This paper describes techniques of statistical inference, in particular likelihood methods, suitable for Markov models incorporating limited time resolution by means of a discrete detection limit. To simplify the analysis, attention is restricted to two-state models, although the methods have more general applicability. Non-uniqueness of the mean open-time and mean closed-time estimators obtained by moment methods based on single exponential approximations to the apparent open-time and apparent closed-time distributions has been reported. The present study clarifies and extends this previous work by proving that, for such approximations, the likelihood equations as well as the moment equations (usually) have multiple solutions. Such non-uniqueness corresponds to non-identifiability of the statistical model for the apparent quantities. By contrast, higher-order approximations yield theoretically identifiable models. Likelihood-based estimation procedures are developed for both single exponential and bi-exponential approximations. The methods and results are illustrated by numerical examples based on literature and simulated data, with consideration given to empirical distributions and model control, likelihood plots, and point estimation and confidence regions.

Ion Channels↗
PubMed1992

Risk, statistical inference, and the law of evidence: the use of epidemiological data in toxic tort cases.

Toxic torts are product liability cases dealing with alleged injuries due to chemical or biological hazards such as radiation, thalidomide, or Agent Orange. Toxic tort cases typically rely more heavily than other product liability cases on indirect or statistical proof of injury. There have been numerous theoretical analyses of statistical proof of injury in toxic tort cases. However, there have been only a handful of actual legal decisions regarding the use of such statistical evidence, and most of those decisions have been inconclusive. Recently, a major case from the Fifth Circuit, involving allegations that Benedectin (a morning sickness drug) caused birth defects, was decided entirely on the basis of statistical inference. This paper examines both the conceptual basis of that decision, and also the relationships among statistical inference, scientific evidence, and the rules of product liability in general.

Abnormalities, Drug-Induced↗
PubMed1991

Practical implications of modes of statistical inference for causal effects and the critical role of the assignment mechanism.

Causal inference in an important topic and one that is now attracting serious attention of statisticians. Although there exist recent discussions concerning the general definition of causal effects and a substantial literature on specific techniques for the analysis of data in randomized and nonrandomized studies, there has been relatively little discussion of modes of statistical inference for causal effects. This presentation briefly describes and contrasts four basic modes of statistical inference for causal effects, emphasizes the common underlying causal framework with a posited assignment mechanism, and describes practical implications in the context of an example involving the effects of switching from a name-band to a generic drug. A fundamental conclusion is that in such nonrandomized studies, sensitivity of inference to the assignment mechanism is the dominant issue, and it cannot be avoided by changing modes of inference, for instance, by changing from randomization-based to Bayesian methods.

Bayes Theorem↗
PubMed1986

Brain asymmetry: facts and fallacies in statistical inference.

In a recent article, C. M. Clark, R. Kessler, and R. Margolin (1985, Brain and Cognition, 4, 7-12) argue that standard statistical tests should not be applied to measures of regional cerebral metabolism. They offer no evidence that such measures uniquely escape the mathematical foundations of statistical inference but, instead, merely note the definitional relations among various descriptive and inferential statistics. They falsely claim that these relations invalidate conclusions drawn from statistical tests, and in making this claim, they commit several quite serious logical fallacies. These fallacies are examined.

Brain Mapping↗
PubMed1975

Statistical inferences about injury and persistence of environmentally stressed bacteria.

A standard technique for ascertaining the survival characteristics of bacteria after being environmentally stressed is to incubate the bacteria on both selective and non-selective media and count the colonies produced. Based on these colony counts, indexes of injury and persistence of the bacteria are calculated. To compare the stress of two different environments, a persistence ratio is calculated. In this paper, methods of statistical inference concerning these indexes and ratios are presented. These statistical methods use well-known procedures for analysis of binomial data and 2 times 2 table data, and are appropriate when the colony counts follow a Possion distribution.

Bacteria↗
PubMed1990

Introduction to biostatistics: Part 4, statistical inference techniques in hypothesis testing.

Statistical methods used to test the null hypothesis are termed tests of significance. Selection of an appropriate test of significance is dependent on the type of data to be analyzed and the number of groups to be compared. Parametric tests of significance are based on the parameters, mean, standard deviation, and variance, and thus are used appropriately when interval or ratio data are analyzed. The t-test and analysis of variance (ANOVA) are examples of parametric tests of significance. Assumptions regarding the data to be analyzed when using the t-test or ANOVA include normality of the populations from which the sample data are drawn, homogeneity of the variances of the populations from which the sample data are drawn, and independence of the data points within a sample group. The t-test is the appropriate test of significance to use if there are only two groups to compare. If there are three or more groups to compare, ANOVA is the appropriate test. ANOVA holds the preset alpha level constant. While ANOVA will imply a significant difference between the groups compared, a multiple comparison test will define which of the three or more groups differ significantly.

Analysis of Variance↗
PubMed1990

Introduction to biostatistics: Part 5, Statistical inference techniques for hypothesis testing with nonparametric data.

Specific statistical tests are used when the null hypothesis (H0) is to be tested using nonparametric nominal or ordinal data. With nominal data, experimental results are expressed by proportions or frequencies. Chi-square or related tests (the Fisher's exact test or the rows by columns test) are appropriate for testing H0 with nominal data. Ordinal data permit arrangement of statistical results by rank. Rank-order tests used to test H0 with ordinal data include the Mann-Whitney U, Kolmogorov-Smirnov, Wilcoxon, Kruskal-Wallis, and Friedman tests. The Kruskal-Wallis and Friedman tests permit multiple intergroup comparisons. Other rank-order tests permit only single intergroup comparisons. Specific details to guide the researcher in the proper selection of these tests are presented.

Statistics as Topic↗
PubMed1987

Statistical inference on spontaneous neuronal discharge patterns. I. Single neuron.

A statistical analysis was performed on extracellularly recorded spike trains of spontaneously active mesencephalic reticular neurons of rats. Only stationary records were used for detailed examination. The moments of interspike intervals were computed, hypothesis of renewal process and its specific forms was tested. Implications for statistical methodology are considered on the basis of the results. The main emphasis is laid on the connection between experimental results and stochastic neuronal models.

Animals↗
PubMed1988

Scientific vs. statistical inference: the problem of multiple contrasts in clinical research.

The problem of type 1 error rates in clinical medicine research is discussed and a new measure of evaluating the incidences of type 1 error is presented. Three measures, including the experimentwise error rate, the error rate per experiment, and the percentage error rate are used to compute the type 1 error in a sample of clinical research. The results suggest the presence of a substantial incidence of type 1 error in the sampled research. The implications for statistical and scientific inferences are briefly discussed and some possible solutions explored.

Research↗
PubMed1988

Statistical inference for infectious diseases. Risk-specific household and community transmission parameters.

A statistical model is presented for the analysis of infectious disease data from family studies in the community. The model partitions the sources of infection into those from within the household and those from the community at large. The parameters reflecting these sources of infection are estimated as functions of the risk factors. This new model is used to overcome problems associated with the lack of independence of observations in infectious disease data and negative confounding due to the association of unmeasured exposures and immunity. An example of how this new statistical model is used to provide a clearer and less confounded description of risk factor effects is presented for data from influenza A(H3N2) epidemic seasons in the Tecumseh Respiratory Illness Study. The risk factors examined are age and pre-epidemic season antibody level as measured by the hemagglutination-inhibition test, while the outcome is the infection rate. A standard analysis of the data indicates that the efficacy of protective antibodies is 70% in children and only 47% in adults. However, such an efficacy measurement is negatively confounded by past exposure which is age dependent. By means of the model, the true, unconfounded, efficacy of protective antibodies is shown to be 90% in both adults and children.

Adolescent↗
PubMed1977

Statistical inference as applied to bioavailability data--a guide for the practicing pharmacist.

Descriptive statistics and statistical tests used in reporting bioavailability data are reviewed in order to give the practicing pharmacist the fundamental knowledge needed to evaluate such data. Using acetaminophen bioavailability data as a model the following concepts are explained: mean, median, mode, standard deviation, range, 95% confidence limit, Student's t-test, analysis of variance, and the Wilcoxon rank sum test.

Acetaminophen↗