Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Sample size estimation”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,207 records · Page 67Linked to original sources
PubMed1980

The estimation of intraclass correlation in the analysis of family data.

The maximum likelihood estimator of the intraclass correlation coefficient rho in samples of unequal size from a multivariate normal distribution has been derived and compared to several other estimators, using Monte Carlo simulation. It is recommended that maximum likelihood be used if no prior knowledge concerning the value of rho is thought to be high. Fow low to moderate values of rho it is recommended that the analysis of variance estimator be used, with those families having only one member deleted from the analysis.

Analysis of Variance↗
PubMed2002

Atmospheric aerosol measurements of 238U and 232Th at Fernald, Ohio, and implications on inhalation dose calculations.

Measurements of the aerosol size distribution of 238U and 232Th at the U.S. Department of Energy's Fernald Environmental Management Project site were made to improve the inhalation dose calculations to off-site individuals. For approximately 1 y an 8-stage cascade impactor was co-located with a high volume sampler and operated at the Fernald Environmental Management Project site to collect aerosol samples. During most of the year, the site was dominated by giant particles with more than 70% of the mass of 238U above 15 microm. The seasonal average of the activity median aerodynamic diameter, based on the impactor samples, which excluded particles >15 microm, for both uranium and thorium was approximately 6.5 microm. These numbers reflect the activities at the site and the domination of the resuspension processes. During most sampling periods the size distribution was bimodal. Thorium concentrations were comparable to the uranium concentrations during the late spring and summer period and decreased to approximately 25% of the 238U concentration in the late summer. Fernald Environmental Management Project is required to calculate the maximum allowable dose from airborne emissions, excluding radon, to meet NESHAP compliance. These calculations assume an AMAD of 1 microm. We found that if you combine size distribution information with the latest ICRP 66 lung model you reduce the estimated dose by a factor of 7. Inclusion of the size distribution of radionuclides at any sampling site would substantially improve the dose estimates to the population.

Aerosols↗
PubMed1996

Mantel-Haenszel-type inference for cumulative odds ratios with a stratified ordinal response.

This article proposes a Mantel-Haenszel-type estimator of an assumed common cumulative odds ratio in a proportional odds model for an ordinal response with several 2 x c contingency tables. It is useful, for instance, for comparing two treatments on an ordinal response for data from several centers when the data are highly sparse. The estimator has behavior similar to the Mantel-Haenszel estimator of a common odds ratio for several 2 x 2 tables. It is consistent under the ordinary asymptotic framework in which the number of tables is fixed and, unlike the maximum likelihood (ML) estimator, also under sparse asymptotics in which the number of tables grows with the sample size. Simulations reveal a considerable difference between it and the ML estimator when each table has few observations. Efficiency comparisons suggest that little efficiency loss occurs compared to the ML estimator when the data are not sparse. Tests and estimators are presented for detecting and handling heterogeneity in the odds ratios, and generalizations are available for stratified r x c contingency tables.

Asthma↗
PubMed1989

Decision rules for selecting effect sizes in meta-analysis: a review and reanalysis of psychotherapy outcome studies.

This study deals with some of the judgmental factors involved in selecting effect sizes from within the studies that enter a meta-analysis. Particular attention is paid to the conceptual redundancy rule that Smith, Glass, and Miller (1980) used in their study of the effectiveness of psychotherapy for deciding which effect sizes should and should not be counted in determining an overall effect size. Data from a random sample of 25 studies from Smith et al.'s (1980) population of psychotherapy outcome studies were first recoded and then reanalyzed meta-analytically. Using the conceptual redundancy rule, three coders independently coded effect sizes and identified more than twice as many of them per study as did Smith et al. Moreover, the treatment effect estimates associated with this larger sample of effects ranged between .30 and .50, about half the size claimed by Smith et al. Analyses of other rules for selecting effect sizes showed that average effect estimates also varied with these rules. Such results indicate that the average effect estimates derived from meta-analyses may depend heavily on judgmental factors that enter into how effect sizes are selected within each of the individual studies considered relevant to a meta-analysis.

Humans↗
PubMed2003

Repeated measures one-way ANOVA based on a modified one-step M-estimator.

Wilcox, Keselman, Muska and Cribbie (2000) found a method for comparing the trimmed means of dependent groups that performed well in simulations, in terms of Type I errors, with a sample size as small as 21. Theory and simulations indicate that little power is lost under normality when using trimmed means rather than untrimmed means, and trimmed means can result in substantially higher power when sampling from a heavy-tailed distribution. However, trimmed means suffer from two practical concerns described in this paper. Replacing trimmed means with a robust M-estimator addresses these concerns, but control over the probability of a Type I error can be unsatisfactory when the sample size is small. Methods based on a simple modification of a one-step M-estimator that address the problems with trimmed means are examined. Several omnibus tests are compared, one of which performed well in simulations, even with a sample size of 11.

Analysis of Variance↗
PubMed2005

[Estimation of allele frequencies in ethnically heterogeneous populations].

A method for reconstructing allele frequencies characteristic of an original ethnically homogeneous population before the start of migration processes is described. Information on both the ethnic group studied and offspring of interethnic marriages is used to estimate the allele frequencies. This makes it possible to increase the informativeness of the sample, which, in the case of ethnic heterogeneity, depends not only on allele frequencies and the total sample size, but also on the ethnic structure of the sample. The problem of estimating allele frequency in an ethnically heterogeneous sample has been solved analytically for diallelic loci. It has been demonstrated that, if offspring of interethnic marriages with the same degree of outbreeding is added to a sample of the ethnic group studied, the sample informativeness does not change. To utilize the information contained in the phenotypes of the offspring of interethnic marriages, representatives of the population from which migration occurs should be included into the sample. The size of the sample ensuring the preassigned accuracy of estimation is minimized at a certain ratio between the numbers of the offspring of interethnic marriages and the "immigrants." To analyze polyallelic loci, a software package has been developed that allows estimating allele frequencies, determining the errors of these estimates, and planning the sample ensuring the preassigned accuracy of estimation. The package is available free at http://mga.bionet.bionet.nsc.ru/PopMixed/PopMixed.html.

Emigration and Immigration↗
PubMed2003

A standardisation of Ciona intestinalis (Chordata, Ascidiacea) embryo-larval bioassay for ecotoxicological studies.

A standardisation of the ascidian Ciona intestinalis embryo-larval bioassay for marine pollution assessment has been developed. The minimum percentage of embryogenesis success was established to assess the quality of the biological material used; minimum sample size and number of replicates per treatment were also estimated. The suitability of artificial and natural seawater for the incubation of ascidian embryos and larvae was compared, and the optimum conditions of temperature, salinity, pH, density of embryos in the vials and the sperm/egg ratio were investigated. On the basis of the 10th percentile of the distribution of larval abnormalities, we proposed a threshold of 50% normal larvae in the control in order to consider the test of acceptable biological quality. According to our results n=5 is a sufficiently high replication to detect 5% differences among treatment means with a power of P=90% and alpha=0.05, and a sampling size >/=222 allows a 95% confidence in the estimate with an error of 0.05. Egg density did not affect larval development within the range 1-20 eggs/ml, and the optimum sperm/egg ratio which fertilise 100% of the eggs was 3000-30,000 sperm/egg (i.e. 10(8)-10(7) sperm/ml). There were not significant differences between the two water types tested, and the optimum tolerance ranges were 18-23 degrees C temperature, 34-42 ppt salinity (42 ppt was the highest salinity tested), and 7.4-8.8 pH. The median effective concentration (EC(50)) of copper (Cu) causing a 50% reduction of normal hatched larvae was 54.2 microg/l (0.85 microM), which shows a sensitivity of this species similar to the commonly used bivalve and sea-urchin tests. The ascidian embryo-larval bioassay is an accurate, reliable, simple and rapid method that can be used in ecotoxicological studies.

Animals↗
PubMed2001

Statistical issues in reporting quality data: small samples and casemix variation.

PURPOSE: To present two key statistical issues that arise in analysis and reporting of quality data. SUMMARY: Casemix variation is relevant to quality reporting when the units being measured have differing distributions of patient characteristics that also affect the quality outcome. When this is the case, adjustment using stratification or regression may be appropriate. Such adjustments may be controversial when the patient characteristic does not have an obvious relationship to the outcome. Stratified reporting poses problems for sample size and reporting format, but may be useful when casemix effects vary across units. Although there are no absolute standards of reliability, high reliabilities (interunit F > or = 10 or reliability > or = 0.9) are desirable for distinguishing above- and below-average units. When small or unequal sample sizes complicate reporting, precision may be improved using indirect estimation techniques that incorporate auxiliary information, and 'shrinkage' estimation can help to summarize the strength of evidence about units with small samples. CONCLUSIONS: With broader understanding of casemix adjustment and methods for analyzing small samples, quality data can be analysed and reported more accurately.

Data Interpretation, Statistical↗
PubMed1993

Bayesian predictive inference for units with small sample sizes. The case of binary random variables.

The National Health Interview Survey is designed to produce precise estimates for the entire United States but not for individual states. In this study, Bayesian predictive inference is used to provide point estimates and measures of variability for the desired finite population quantities. The investigation reported here concerns binary random variables such as the occurrence of at least one doctor visit within the past 12 months. The specification is hierarchic. First, for each cluster, there is a separate logistic regression relating a patient's probability of a doctor visit with his or her characteristics. Second, there is a multivariate linear regression linking the (cluster) regression parameters to covariates measured at the cluster level. A fully Bayesian analysis is carried out; this technique provides gains over synthetic estimation and conventional randomization-based analysis. The reported approach is potentially useful for any situation when the sample size associated with a unit of interest (e.g., a hospital or small geographic area) is too small to permit satisfactory inference using only the data from that unit.

Bayes Theorem↗
PubMed2003

Matched-pair noninferiority trials using rate ratio: a comparison of current methods and sample size refinement.

In this article, we consider the establishment of noninferiority between a reference test and a new test with respect to the ratio of sensitivity and/or specificity. We first review two (one-sided) noninferiority tests, namely the logarithmic transformation test and the Fieller-type test, and their associated sample size formulae proposed for matched-pair designs when the null hypothesis is of a specified nonunity rate ratio. Different methods for implementing these one-sided noninferiority tests are reviewed. They include (1) the sample-based method, (2) the constrained least-squares estimation method, and (3) the constrained maximum likelihood estimation method. We conduct a simple empirical study to evaluate the performance of various tests/methods. In summary, statistics based on constrained maximum likelihood estimation always control the actual type I error rate much better than other statistics. Moreover, the corresponding approximate sample size formulae are valid asymptotically in the sense that the exact powers associated with the approximate sample size formulae are generally close to the prespecified power level. Methods based on constrained maximum likelihood estimation are illustrated with a real example from a clinical laboratory study.

Clinical Trials as Topic↗
PubMed1994

Assessment of ecologic regression in the study of lung cancer and indoor radon.

Ecologic regression studies conducted to assess the cancer risk of indoor radon to the general population are subject to methodological limitations, and they have given seemingly contradictory results. The authors use simulations to examine the effects of two major methodological problems that affect these studies: measurement error and misspecification of the risk model. In a simulation study of the effect of measurement error caused by the sampling process used to estimate radon exposure for a geographic unit, both the effect of radon and the standard error of the effect estimate were underestimated, with greater bias for smaller sample sizes. In another simulation study, which addressed the consequences of uncontrolled confounding by cigarette smoking, even small negative correlations between county geometric mean annual radon exposure and the proportion of smokers resulted in negative average estimates of the radon effect. A third study considered consequences of using simple linear ecologic models when the true underlying model relation between lung cancer and radon exposure is nonlinear. These examples quantify potential biases and demonstrate the limitations of estimating risks from ecologic studies of lung cancer and indoor radon.

Bias↗
PubMed2003

How should subgroup analyses affect clinical practice? Insights from the Metoprolol Succinate Controlled-Release/Extended-Release Randomized Intervention Trial in Heart Failure (MERIT-HF).

CONTEXT: The Metoprolol CR/XL Randomized Intervention Trial in Chronic Heart Failure (MERIT-HF), the Cardiac Insufficiency Bisoprolol Study II (CIBIS-II), and the Carvedilol Prospective Randomized Cumulative Survival Study (COPERNICUS) have all demonstrated highly significant positive effects on total mortality as well as total mortality plus all-cause hospitalization in patients with heart failure. While none of these trials are large enough to provide definitive results in any particular subgroup, it is of interest for physicians to examine the consistency of results as regards efficacy and safety for various subgroups or risk groups. OBJECTIVE: To summarize results from both predefined as well as post-hoc subgroup analyses performed in the MERIT-HF trial, and to provide guidance as to whether any subgroup is at increased risk, despite an overall strongly positive effect, and to discuss the difficulties and limitations in conducting such subgroup analyses. For some subgroups we performed metaanalyses with data from the CIBIS II and COPERNICUS trials in order to obtain more robust data on mortality in subgroups with a small number of deaths (e.g. for women). SETTING: MERIT-HF was run in 14 countries, and randomized a total of 3,991 patients with symptomatic systolic heart failure (NYHA class II to IV with ejection fraction < or =0.40). Treatment was initiated with a very low dose with careful titration to a maximum target dose of 200 mg metoprolol succinate controlled release/extended release (CR/XL), or highest tolerated dose. MAIN OUTCOME MEASURES: Total mortality (first primary endpoint), total mortality plus all-cause hospitalization (second primary endpoint), and total mortality plus hospitalization for heart failure (first secondary endpoint) analyzed on a time to first event basis. RESULTS: Overall, MERIT-HF demonstrated a 34% reduction in total mortality ( p = 0.00009 nominal) and a 19% reduction for mortality plus all-cause hospitalization ( p = 0.00012). The first secondary endpoint of mortality plus hospitalization for heart failure was reduced by 31% ( p = 0.0000008). The results were remarkably consistent for both primary outcomes and the first secondary outcome across all predefined subgroups as well as nearly all post-hoc subgroups. Metoprolol CR/XL has been very well tolerated, overall as well as in all subgroups analyzed. Overall 87% of the patients reached a dose of 100 mg or more of metoprolol CR/XL once daily, and 64% reached the target dose of 200 mg once daily. CONCLUSION: Our results show that when carefully titrated, metoprolol CR/XL can safely be instituted for the overwhelming majority of outpatients with clinically stable systolic heart failure, with minimal side effects or deterioration. The time has come to overcome the barriers that physicians perceive to beta-blocker treatment, and to provide it to the large number of patients with heart failure in need of this therapy, including also high risk patients like elderly patients, patients with severe heart failure, and patients with diabetes. Because of the increased risk, these are the patients in whom treatment will have the greatest impact as shown by number of lives saved and number of hospitalizations avoided. The target dose should be strived for in all patients who tolerate this dose. We should expect some variation of the treatment effect around the overall estimate as we examine a large number of subgroups due to small sample size in subgroups and due to chance. However, we believe that the best estimate of treatment effect for any particular subgroup should be the overall effect observed in the trial.

Adrenergic beta-Antagonists↗
PubMed1981

On the relative efficiencies of alternative ratio estimators for morphometric analysis of cell membrane surface features.

For morphometric analysis of desmosomes, synapses and other membrane surface features, estimating component densities on a reference surface (the membrane with which they are associated) often provides a useful practical alternative to estimating densities in a reference volume (the tissue in which they are enclosed). The present report assesses the relative efficiencies of these two approaches. In particular, the efficiencies of stereological estimators for component numerical density on a surface (NS) and in a volume (NV) are compared, together with those for the surface densities SS and SV. For this purpose, a morphometric model developed for characterizing desmosomes in human forearm skin was quantified by point and intersection counting. The efficiencies of the alternative ratio estimators were evaluated by comparing their coefficients of variation obtained on samples of equivalent size and having a similar overall analysis time. Various types of bias influencing the results are also discussed. The results demonstrate that estimators of component densities on a surface are superior to those of densities in a volume when studying epidermal desmosomes. For a given size of sample they offer a smaller coefficient of variation. In other words, they are more efficient. They may be even more advantageous in other experimental situations.

Cell Membrane↗
PubMed1983

Storage of red cell concentrates in CPD-A2 for 42 and 49 days.

CPD-A2 is a modified CPD blood preservative with adenine, containing 1 1/2 times as much glucose as CPD. Units (450 ml) of blood from 21 normal donors were collected in CPD-A2 in plastic bags and held at room temperature for 8 hr. An 80% red cell concentrate was prepared and this was stored for 42 or 49 days at 4 degrees C, with the containers in either a standing or lying position. Measurements of glucose consumption, red cell ATP, and 2,3-DPG and of plasma hemoglobin, pH, Na+, and K+ were performed on all samples. The size of the "fragile tail" of osmotically fragile red cells was estimated in 12 samples. The poststorage 24 hr viability of their own stored 51Cr-tagged red cells was documented in 19 of the volunteers. At least 4 months after the original donation, a second unit of blood was collected from eight of the donors to make possible intradonor comparison of the biochemical effects of storage position. After 42 days but not after 49 days of storage, red cells in concentrates stored in the lying position had consumed more glucose and had a higher poststorage pH than did cells stored in the standing position. The poststorage 24 hr viability of red cells stored for 42 days averaged 83.6%, with all units exceeding 70% viability. At 49 days the average viability was 69.1%. Although the average viability of cells stored in the lying position for 42 days was higher than that of concentrates stored standing, the difference was not statistically significant at the 5% level. The plasma hemoglobin level showed a weak correlation with viability of stored cells. Red cell ATP levels were correlated with viability only at 42 days' and not at 49 days' storage. Concentrates of red cell collected in CPD-A2 manifested fully satisfactory viability for 42 days. At 49 days storage the results of viability studies were borderline. High plasma hemoglobin values are observed at both 42 and 49 days' storage and may limit the usefulness of red cell concentrates stored for prolonged periods of time.

2,3-Diphosphoglycerate↗
PubMed2002

Power calculations for genetic association studies using estimated probability distributions.

The determination of the power of-or of an appropriate sample size for-genetic association studies that exploit linkage disequilibrium requires many assumptions. Some of the more important assumptions include the linkage-disequilibrium strength among alleles at the observed marker-locus sites and a potential trait-influencing locus, the frequencies of the marker locus and trait-influencing alleles, and the ultimate density of the marker locus "map" (i.e., the number of bases between marker loci) necessary in order to identify, with some confidence, trait-influencing alleles. I consider an approach to assessment of the power and sample-size requirements of genetic case-control association study designs that makes use of empirically derived estimates of the distributions of important parameters often assumed to take on arbitrary values. My proposed methodology is extremely general and flexible and ultimately can provide realistic answers to questions such as "How many markers and/or how many individuals might it take to identify, with confidence, a disease gene, via linkage-disequilibrium and association methods from a candidate region or whole genome perspective?" I showcase aspects of the proposed methodology, using information abstracted from the literature.

Alleles↗
PubMed2006

Sample size calculation in survival trials accounting for time-varying relationship between noncompliance and risk of outcome event.

BACKGROUND: Most methods of sample size calculations for survival trials adjust the estimated outcome event rates for noncompliance based on the assumption that non-compliance is independent of the risk of the outcome event although there has been published evidence that noncompliers are often at a higher risk than compliers. More recent work has started to consider the situations of informative noncompliance and different risks for noncompliers. However, the possibility of a time-varying association between noncompliance and risk has been ignored. Our analysis indicated a strong time-varying relationship between noncompliance defined as permanent discontinuation of study treatments and risk of the outcome event in the CONVINCE trial. PURPOSE: The purpose of this research is to develop methods for the log-rank sample size calculations for two-arm clinical trials that allow for the relationship between risk and noncompliance to vary over time and to study how sample size requirements vary with different patterns of the time relationship. METHODS: The method developed takes Lakatos' Markov chain approach as a basis, modifying it to incorporate time dynamics, and emphasizing permanent discontinuation of study medication as the form of noncompliance to be considered. RESULTS: Results with our method show that sample size depends on the relative rates of noncompliance in the two arms, the hazard for the outcome event following non-compliance, whether it involves switching to the hazard of the opposite arm or is common to both arms, and whether noncompliance occurs early or late in the trial. These factors interact with each other in complex ways, precluding simple summaries. LIMITATIONS: This research focuses on two-arm clinical trials with time to event as primary outcome measure. The method developed is not directly applicable to trials with more complicated designs and/or trials with other types of primary outcome. CONCLUSIONS: The pattern of the relationship between noncompliance and risk can have a dramatic impact on the sample size and power calculations in survival studies. The method introduced provides a useful tool for investigators to explore the optimal sample size accounting for various dynamic associations between noncompliance and risk.

Clinical Trials as Topic↗
PubMed2000

Large-sample confidence intervals for validity and reliability coefficients.

Large-sample confidence intervals (CI) for reliability, validity, and unattenuated validity are presented. The CI for unattenuated validity is based on the Bonferroni inequality, which relies on one CI for test-retest reliability and one for validity. Covered are four reliability-validity situations: (a) both estimates were from random samples; (b) reliability was from a random sample but validity was from a selected sample; (c) validity was from a random sample but reliability was from a selected sample; and (d) both estimates were from selected samples. All CIs were evaluated by using a simulation. CIs on reliability, validity, or unattenuated validity are accurate as long as selection ratio is at least 20% and selected sample size is 100 or larger. When selection ratio is less than 20%, estimators tend to underestimate their parameters.

Confidence Intervals↗
PubMed1999

Capture-recapture method for estimating misclassification errors: application to the measurement of vaccine efficacy in randomized controlled trials.

BACKGROUND: The measure of efficacy is optimally performed by randomized controlled trials. However, low specificity of the judgement criteria is known to bias toward lower estimation, while low sensitivity increases the required sample size. A common technique for ensuring good specificity without a drop in sensitivity is to use several diagnostic tests in parallel, with each of them being specific. This approach is similar to the more general situation of case-counting from multiple data sources, and this paper explores the application of the capture-recapture method for the analysis of the estimates of efficacy. METHOD: An illustration of this application is derived from a study on the efficacy of pertussis vaccines where the outcome was based on > or =21 days of cough confirmed by at least one of three criteria performed independently for each subject: bacteriology, serology, or epidemiological link. Log-linear methods were applied to these data considered as three sources of information. RESULTS: The best model considered the three simple effects and an interaction term between bacteriology and epidemiological linkage. Among the 801 children experiencing > or =21 days of cough, it was estimated that 93 cases were missed, leading to a corrected total of 413 confirmed cases. The relative vaccine efficacy estimated from the same model was 1.50 (95% confidence interval: 1.24-1.82), similar to the crude estimate of 1.59 and confirming better protection afforded by one of the two vaccines. CONCLUSION: This method allows supporting analysis to interpret primary estimates of vaccine efficacy.

Adolescent↗