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PubMed1991

Hypothesis-testing abilities of language-impaired children.

Hypothesis-testing abilities were assessed using a modification of the discrimination-learning paradigm employed by Nelson, Kamhi, and Apel (1987) that was designed to minimize the short-term memory demands of the task. Sixteen language-impaired and 16 normal-language children in kindergarten and first and second grades participated in the study. The language-impaired children solved significantly fewer problems than normal-language controls equated on cognitive level, but the two groups used similar hypothesis types to solve the problems. Type of verbal feedback provided during the hypothesis testing task (explicit vs. nonexplicit) did not significantly affect the performance of either group. These results are interpreted as indicating that language-impaired children demonstrate inefficient use of problem-solving strategies that cannot be attributed solely to memory difficulties. Issues surrounding the investigation of language-impaired children's cognitive abilities are discussed.

Child↗
PubMed2002

Teaching hypothesis tests--time for significant change?

Confusion in the teaching of statistical inference dates back to the conflict of Fisher's P-values and significance tests with the Neyman-Pearson hypothesis testing approach. To avoid the well-known pitfalls arising from over-reliance on significance tests and the division of results into 'significant' or 'not significant', many medical journals now insist that presentation of statistical analyses includes confidence intervals as well as or instead of P-values. The confusion over how to report statistical analyses which is evident in the recent medical literature is matched by divergent teaching of hypothesis tests between the 16 U.K. medical schools represented at the April 2000 Burwalls meeting. Suggested guidelines for the teaching of statistical inference to medical students are presented, and possible future developments are discussed.

Confidence Intervals↗
PubMed1998

Activation of different anterior cingulate foci in association with hypothesis testing and response selection.

Much everyday behavior is implicitly guided by hypotheses about the world which are monitored and updated in the light of changing circumstances. The process of translating these hypotheses into behavior typically involves implementing choices, often based on incompletely specified information. The present study aimed at modeling these processes to determine the neural substrates of hypothesis testing and, in particular, how these are modulated by the requirement to make choices. We used positron emission tomography to study six right-handed volunteers performing an insoluble hypothesis testing task in which subjects attempted to identify a rule determining which of two black and white checkerboard stimuli was correct. This task was compared with a control task matched for perceptuomotor requirements, but involving no hypothesis testing. Both tasks were performed with or without a requirement to make a choice. Structures activated in association with hypothesis testing included the cerebellum, left anterior cingulate, right precuneus, right thalamus, and left inferior frontal gyrus. The requirement to choose a response was associated with activation of the left anterior cingulate and right lateral orbitofrontal cortex. A significant modulation of activation associated with hypothesis testing was observed in the anterior cingulate region that was also activated by making a choice. These findings are discussed in terms of the neural substrates of complex "executive" tasks. We argue that the precise cognitive parameters of such tasks, and specifically the requirement to implement decisions in actual behavior, are critical in determining the associated neural response.

Adult↗
PubMed1996

Sensible hypothesis testing in deluded, depressed and normal subjects.

BACKGROUND: Previous research has indicated that deluded patients may experience difficulties when testing hypotheses. In this study, hypothesis-testing strategies were assessed in patients with persecutory delusions, depressed patients and normal controls. METHOD: Subjects were presented problem items describing typical everyday situations with either positive or negative outcomes and were required to choose strategies to prove that one of three variables was responsible for the outcomes. RESULTS: Consistent with previous research into sensible reasoning, subjects chose to manipulate the variable hypothesised to be responsible for the outcome (disconfirmation strategy) more when the outcome was negative than when it was positive, and chose to manipulate the remaining variables (confirmation strategy) more when the outcome was positive. No group differences were observed. CONCLUSIONS: No evidence was found of abnormal hypothesis-testing strategies in deluded patients.

Adult↗
PubMed1990

Ventricular tachycardia and fibrillation detection by a sequential hypothesis testing algorithm.

An algorithm for detecting ventricular fibrillation (VF) and ventricular tachycardia (VT) by the method of sequential hypothesis testing is presented. The algorithm first generates a binary sequence by comparing the signal to a threshold. The probability distribution of the time intervals of the binary sequence is obtained, and Wald's sequential hypothesis testing procedure is next employed to discriminate the arrhythmias. Sequential hypothesis testing of 85 cases resulted in identification of 1) 97.64% VF and 97.65% VT episodes after 5 s, and 2) 100% identification of both VF and VT after 7 s. The desired false positive and false negative error probabilities can be preprogrammed into the algorithm. An important feature of the sequential method is that extra time for detection can be traded off for improved accuracy, and vice versa.

Algorithms↗
PubMed1998

Statistical Inference (Part 3): Statistical Hypothesis Testing and Confidence Interval Estimation.

An association between an independent and a dependent variable found in a study may have several explanations, including chance (i.e., random error). This article presents two approaches to assess the role played by chance in an association: confidence interval estimation and statistical hypothesis testing. Statistical hypothesis testing estimates the probability (i.e., the P value) of getting a difference as large or larger than the one observed in a specific study assuming the absence of association. Confidence intervals are estimates of the range of values that are expected to include the actual parameter with a certain probability, or confidence level (often 0.95 or 95%).

Journal Article↗
PubMed2006

The role of responsibility and fear of guilt in hypothesis-testing.

Recent theories argue that both perceived responsibility and fear of guilt increase obsessive-like behaviours. We propose that hypothesis-testing might account for this effect. Both perceived responsibility and fear of guilt would influence subjects' hypothesis-testing, by inducing a prudential style. This style implies focusing on and confirming the worst hypothesis, and reiterating the testing process. In our experiment, we manipulated the responsibility and fear of guilt of 236 normal volunteers who executed a deductive task. The results show that perceived responsibility is the main factor that influenced individuals' hypothesis-testing. Fear of guilt has however a significant additive effect. Guilt-fearing participants preferred to carry on with the diagnostic process, even when faced with initial favourable evidence, whereas participants in the responsibility condition only did so when confronted with an unfavourable evidence. Implications for the understanding of obsessive-compulsive disorder (OCD) are discussed.

Adult↗
PubMed2006

Testing equivalence between two laboratories or two methods using paired-sample analysis and interval hypothesis testing.

A modified interval hypothesis testing procedure based on paired-sample analysis is described, as well as its application in testing equivalence between two bioanalytical laboratories or two methods. This testing procedure has the advantage of reducing the risk of wrongly concluding equivalence when in fact two laboratories or two methods are not equivalent. The advantage of using paired-sample analysis is that the test is less confounded by the intersample variability than unpaired-sample analysis when incurred biological samples with a wide range of concentrations are included in the experiments. Practical aspects including experimental design, sample size calculation and power estimation are also discussed through examples.

Laboratories↗
PubMed1976

Familial aggregation of chronic respiratory disease: use of National Health Interview Survey data for specific hypothesis testing.

The 1970 National Health Interview Survey included questions on respiratory disease and smoking habits. The new data were released in July 1974. Data consisted of information on approximately 116,000 persons from 37,000 households selected randomly from 357 primary sampling units. To test a hypothesis about familial clustering of chronic respiratory disease in households, we selected as index households those having an adult (aged 35-54 years) reporting a diagnosis of asthma, bronchitis, or emphysema and also having first order relatiaves less than age 35. Index households were matched with households from the same neighbourhood having an adult aged 35-54, of the same sex as the diseased person in the index household, without disease and with all other adults 35-54 without disease, and which had first order relatives less than 35 living in the same household. Analysis was carried out using Cochran's d-test to compare frequency of respiratory disease in persons less than 35 in each group. There was a strong association (P less than .001) between persons over 35 with chronic respiratory diseases and the disease rate in their first order relatives. The association could not be explained by differences in demographic variables and smoking habits.

Adolescent↗
PubMed2006

Chewing gum and risk of oesophageal adenocarcinoma: a new hypothesis tested in a population-based study.

The aim of this study was to test the hypothesis that chewing gum is associated with risk of oesophageal and cardia adenocarcinoma. A Swedish nationwide, population-based, case-control study was conducted in 1995-1997. All patients were prospectively and uniformly documented and classified shortly after diagnosis. In all, 189 and 262 patients with oesophageal and cardia adenocarcinoma, respectively, and 820 population-based control subjects were interviewed. These patients together constituted 85% of eligible cases occurring in Sweden. Odds ratios (OR) with 95% confidence intervals (CI) were calculated by multivariable logistic regression with adjustment for plausible confounders. Regular users of chewing gum (P3 times/week for P6 months) were not at increased risk of oesophageal adenocarcinoma (OR 1.0, 95% CI 0.6-2.2), and no duration-response relation was observed (P = 0.38). No association between regular gum chewing and cardia adenocarcinoma was found (OR 1.0, 95% CI 0.6-1.7), irrespective of duration of use (P = 0.56). In conclusion, with regard to risk of oesophageal or cardia adenocarcinoma, gum chewing seems harmless.

Adenocarcinoma↗
PubMed2002

Hypothesis testing as a laboratory exercise: a simple analysis of human walking, with a physiological surprise.

This paper describes a laboratory exercise designed to provide students with experience testing a hypothesis by systematically isolating and controlling determinant variables. The study involves an analysis of walking and is performed by the students on a subject from within their lab group. The study requires use of a motorized treadmill, tape measure, stop watch, metronome, personal cassette player, and calculator. The exercise is designed to include factors that the students are familiar with, so they can focus on the isolation of variables without being confused about the process they are investigating. However, the exercise will not turn out as the students anticipate, meaning they will be forced to reevaluate the assumptions that formed the basis of their original hypothesis. This exercise is designed for a college-level course in exercise science, physiology, or biology but could easily be managed by a high school honors class with appropriate guidance.

Adult↗
PubMed2006

Alternatives to statistical hypothesis testing in ecology: a guide to self teaching.

Statistical methods emphasizing formal hypothesis testing have dominated the analyses used by ecologists to gain insight from data. Here, we review alternatives to hypothesis testing including techniques for parameter estimation and model selection using likelihood and Bayesian techniques. These methods emphasize evaluation of weight of evidence for multiple hypotheses, multimodel inference, and use of prior information in analysis. We provide a tutorial for maximum likelihood estimation of model parameters and model selection using information theoretics, including a brief treatment of procedures for model comparison, model averaging, and use of data from multiple sources. We discuss the advantages of likelihood estimation, Bayesian analysis, and meta-analysis as ways to accumulate understanding across multiple studies. These statistical methods hold promise for new insight in ecology by encouraging thoughtful model building as part of inquiry, providing a unified framework for the empirical analysis of theoretical models, and by facilitating the formal accumulation of evidence bearing on fundamental questions.

Algorithms↗
PubMedDate not supplied

Multiple hypothesis tests in multiple investigations.

Inferential statistical methods have traditionally been based on the assumption that one experiment is performed and that interest centres on one or more predetermined hypothesis tests. Exploratory research, on the other hand, often involves multiple hypotheses or repeated investigations under similar or different conditions or both. Several techniques have been proposed to deal with multiple or simultaneous hypothesis testing in single investigations, and procedures to combine observed significance levels for an individual hypothesis test from two or more investigations have been suggested. In this paper we propose a method for identifying important results from multiple statistical tests in multiple investigations. The method is illustrated by using high performance liquid chromatography to identify potential aetiologic contaminants in L-tryptophan samples.

Chromatography, High Pressure Liquid↗
PubMed2000

Answering two criticisms of hypothesis testing: a comment.

In a recent article, Leventhal (1999) responds to two criticisms of hypothesis testing by showing that the one-tailed test and the directional two-tailed test are valid, even if all point null hypotheses are false and that hypothesis tests can provide the probability of decisions being correct which are based on the tests. Unfortunately, the falseness of all point null hypotheses affects the operating characteristics of the directional two-tailed test, seeming to weaken certain of Leventhal's arguments in favor of this procedure.

Humans↗
PubMed2006

A comparison of mean partialing and dual-hypothesis testing to evaluate stereotype effects when assessing profile similarity.

Assessing profile similarity is an important task in research and clinical practice, but conclusions about profile similarity may be confounded by stereotype effects that create artificially similar profiles. In this article, we review the impact of stereotype effects on profile similarity and a conventional approach to addressing this confound (i.e., mean partialing). We argue that a dual-hypothesis testing approach distinguishing the no-effect null hypothesis (i.e., is the observed similarity different from zero?) from the chance-effect null hypothesis (i.e., is the observed similarity different from chance given the distribution of profile elements?) can provide a more nuanced understanding of profile similarity. To compare results from these 2 perspectives, we analyzed data from 2 samples using within-persons correlations as indexes of similar profile shapes. Results indicated that a dual-hypothesis testing approach led to more conservative conclusions about profile similarity (i.e., fewer Type 1 errors) than mean partialing and may be especially valuable when dealing with moderate-sized stereotype effects. Both approaches led to identical conclusions when stereotype effects were largest. Conclusions emphasize the relative merits and limitations of the dual-hypothesis testing approach as well as potential future applications in the personality assessment domain.

Adolescent↗
PubMed1985

Conditioned suppression tests of the context-blocking hypothesis: testing in the absence of the preconditioned context.

Two experiments are reported that use rats in a conditioned suppression situation. The experiments, designed to remove confounds that have complicated interpretations of prior research, tested the context-blocking hypothesis, the proposition that static apparatus cues or conditioning contexts can block conditioning to discrete conditioned stimuli (CSs). Experiment 1, like previous work, tested for conditioning to the target CS in the same context that had been preconditioned and in which target conditioning had occurred; the experiment demonstrated a context-blocking like effect. Experiment 2 tested for conditioning not only in the preconditioned context but also in a nonpreconditioned context. Evidence for context blocking appeared similar in the two test situations. This suggests that conditioned contexts block the acquisition of associative strength by discrete CSs at the time of target conditioning (e.g., Rescorla & Wagner, 1972) and not through performance factors at the time of testing (e.g., Gibbon & Balsam, 1981).

Animals↗