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Results for “Statistical Power”

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At least 163 records · Page 9Linked to original sources
PubMed1990

Statistical significance and statistical power in hypothesis testing.

Experimental design requires estimation of the sample size required to produce a meaningful conclusion. Often, experimental results are performed with sample sizes which are inappropriate to adequately support the conclusions made. In this paper, two factors which are involved in sample size estimation are detailed--namely type I (alpha) and type II (beta) error. Type I error can be considered a "false positive" result while type II error can be considered a "false negative" result. Obviously, both types of error should be avoided. The choice of values for alpha and beta is based on an investigator's understanding of the experimental system, not on arbitrary statistical rules. Examples relating to the choice of alpha and beta are presented, along with a series of suggestions for use in experimental design.

Research Design↗
PubMed2006

Detecting dissociations in single-case studies: Type I errors, statistical power and the classical versus strong distinction.

Dissociations observed in single-case studies play an important role in building and testing theory in neuropsychology; therefore the criteria used to identify their presence should be subjected to empirical scrutiny. Extending work on classical dissociations, Monte Carlo simulation is used to examine the Type I error rate for two methods of detecting strong dissociations. When a Type I error was defined as misclassifying a healthy control, error rates were low for both methods. When Type I errors were defined as misclassifying patients with strictly equivalent deficits on two tasks, error rates for strong dissociations were high for the "conventional" criteria and were very high when cases misclassified as exhibiting either form of dissociation (strong or classical) were combined (maximum = 55.1%). The power to detect strong and classical dissociations was generally low-to-moderate, but was moderate-to-high in most scenarios when power was defined as the ability to detect either form of dissociation. In most scenarios patients with strong dissociations were more likely to be classified as exhibiting classical dissociations. The results question the practical utility of the distinction between strong and classical dissociations regardless of the criteria employed to test for their presence.

Case-Control Studies↗
PubMed1996

Sample size and statistical power in [15O]H2O studies of human cognition.

Determining the appropriate sample size is a crucial component of positron emission tomography (PET) studies. Power calculations, the traditional method for determining sample size, were developed for hypothesis-testing approaches to data analysis. This method for determining sample size is challenged by the complexities of PET data analysis: use of exploratory analysis strategies, search for multiple correlated nodes on interlinked networks, and analysis of large numbers of pixels that may have correlated values due to both anatomical and functional dependence. We examine the effects of variable sample size in a study of human memory, comparing large (n = 33), medium (n = 16,17), small (n = 11, 11, 11), and very small (n = 6,6,7,7,7) samples. Results from the large sample are assumed to be the "gold standard." The primary criterion for assessing sample size is replicability. This is evaluated using a hierarchically ordered group of parameters: pattern of peaks, location of peaks, number of peaks, size (volume) of peaks, and intensity of the associated t (or z) statistic. As sample size decreases, false negatives begin to appear, with some loss of pattern and peak detection; there is no corresponding increase in false positives. The results suggest that good replicability occurs with a sample size of 10-20 subjects in studies of human cognition that use paired subtraction comparisons of single experimental/baseline conditions with blood flow differences ranging from 4 to 13%.

Adult↗
PubMedDate not supplied

Effectiveness research and implications for study design: sample size and statistical power.

Most clinical trials have started to incorporate more broadly defined outcome measures, such as health-related quality of life, to complement clinical status measures as well as direct costs and cost-effectiveness analyses. Contrasting a broad range of outcome and cost measures, we analyze the implications for sample sizes and study design using data from prior mental health and primary care studies that span a wide range of practice settings, patient populations, and geographic areas. While meaningful clinical symptomatic differences are often detectable with sample sizes of well under 100 per cell, detecting even large changes in health-related quality of life generally requires several hundred observations per cell. Reasonable precision in cost estimates usually requires sample sizes in the thousands. Very few clinical trials or observational effectiveness studies that incorporate quality of life or cost measures have such sample sizes, resulting in many (unreported) null findings and, due to publication biases favoring significant results, scientific publications that exaggerate true effects. It raises issues for the general direction of clinical trials and effectiveness studies, as well as for how cost and health-related quality of life results based on small studies should be dealt with in publications.

Clinical Trials as Topic↗
PubMedDate not supplied

Statistical power and design of focused clustering studies.

Focused clustering studies investigate raised incidence of disease in the vicinity of prespecified putative sources of increased risk. The analytic power functions of three focused tests of disease clustering are defined and used to address two design issues related to focused cluster studies. The power functions provide sample sizes required to detect a given increase in relative risk and allow measurement of the effects of aggregating data when a fixed underlying cluster model is assumed. Results are illustrated on hypothetical data as well as leukaemia data from upstate New York.

Cluster Analysis↗
PubMed1996

Assessing the statistical power to detect linkage in a sample of 51 bipolar affective disorder pedigrees.

We used computer simulation method to address the question of power in an initial collaborative sample of 51 bipolar affective disorder pedigrees. Simulations were performed for all possible combinations using (1) two levels of diagnostic stringency, (2) three transmission models, (3) locus heterogeneity, and (4) different assumed phenocopy rates. Some of the factors affect the power to detect linkage are (1) the specification of the correct genetic model, (2) the degree of locus heterogeneity, and (3) the frequency of phenocopies. The first two assertions were supported by our simulation results, but varying the rates of phenocopy did not substantially alter the power of the sample until a critical point. However, it is important to point out that these results are dependent on the genetic models under study and on the use of the "correct" model (i.e., the one used to simulate the data). If we assume a dominant mode of inheritance and locus homogeneity, the power to detect linkage is 97.5% at a theta of .01. However, the power declines dramatically, to 60.5% and 14.7%, if only 75 and 50% of the families are linked, respectively. Locus heterogeneity has a similar effect on the power of the sample to exclude linkage. The relative lack of power in our data, in the presence of significant locus heterogeneity, and for an intermediate mode of inheritance, underscores the need for multicenter collaboration.

Adolescent↗
PubMedDate not supplied

[Oral contraceptives and breast cancer: analysis of the statistical power of the association].

The power of the association between oral contraceptives and breast cancer was analysed in all the papers published up to date. Seventy-seven publications (from 44 studies) were collected and graded as to quality using meta-analytical methods. Power achieved a figure of greater than or equal to 0.8 in a 10.8% of the associations studied. It showed a significant relationship with the existence of a significant relative risk of the oral contraceptives for breast cancer. The relationship with the sample size of a study was not linear. Power did not show any significant relationship to other variables related to the design of a study (apart from matching, being the power higher in unmatched studies), or to the biases detected, although studies considered as unbiased yielded a higher power. Logistic regression analysis included as predictors of a power greater than or equal to 0.80 the existence of a significant relative risk and the lack of biases in a research.

Analysis of Variance↗
PubMed2000

Statistical power and optimal design for multisite randomized trials.

The multisite trial, widely used in mental health research and education, enables experimenters to assess the average impact of a treatment across sites, the variance of treatment impact across sites, and the moderating effect of site characteristics on treatment efficacy. Key design decisions include the sample size per site and the number of sites. To consider power implications, this article proposes a standardized hierarchical linear model and uses rules of thumb similar to those proposed by J. Cohen (1988) for small, medium, and large effect sizes and for small, medium, and large treatment-by-site variance. Optimal allocation of resources within and between sites as a function of variance components and costs at each level are also considered. The approach generalizes to quasiexperiments with a similar structure. These ideas are illustrated with newly developed software.

Health Care Rationing↗
PubMed1999

The VECAT study: methodology and statistical power for measurement of age-related macular features. Vitamin E, Cataract, and Age-related Maculopathy Study.

PURPOSES: (1) To develop the methodology for the grading of macular one-frame stereoslides and to assess the reliability of the system. (2) To determine the prevalence of soft drusen (> 63 microm) and pigment abnormalities synonymous with age-related maculopathy (ARM) at baseline, in a clinical trial of volunteers aged between 55 and 80 years of age. (3) To ascertain the power of the study to detect the 4-year incidence and progression of ARM in vitamin E versus placebo treated participants, given the baseline prevalence. METHODS: The 1204 participants enrolled in the Vitamin E, Cataract, and Age-related Maculopathy Study (VECAT) had colour stereoslides of their fundus taken using the Nidek 3-DX mydriatic fundus camera. The stereoslides were graded by two masked graders according to the "International Classification System for ARM and AMD". Assessment of inter- and intra-observer reliability was carried out on a regular basis on 15% of randomly selected slides. Anticipated rates of incidence and progression were based on results reported by the Beaver Dam Eye Study and the Chesapeake Bay Waterman Study. Power estimations were determined using the "nQuery Advisor" software program. Analyses were carried out on the worse affected eye. RESULTS: Inter-observer reliability was moderate to substantial (Kappa 0.5-0.88) whilst intra-observer agreement was high (0.6-1.0). The prevalence of any soft drusen was 32%. Significant associations were found between soft large indistinct drusen, hypopigmentation, hyperpigmentation and age (p = 0.0001, 0.024 and 0.0001, respectively). The study has at least 87% power to detect an odds ratio equal to two for the progression of soft distinct, soft indistinct, hyperpigmentation and hypopigmentation. CONCLUSIONS: The VECAT study methodology appears to be highly reliable and to have sufficient power to detect the differences in the four-year progression of soft distinct and indistinct drusen and pigment abnormalities between the treatment groups.

Aged↗