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At least 379 records · Page 21Linked to original sources
PubMed2004

Sample size calculations in acute stroke trials: a systematic review of their reporting, characteristics, and relationship with outcome.

BACKGROUND AND PURPOSE: Only a few randomized controlled trials in acute stroke have shown a treatment-related benefit. Inadequate trial design, especially low sample size, may partly explain this failure. We investigated sample size calculations (SSCs) in a systematic review of acute stroke trials. METHODS: Full reports of nonconfounded randomized controlled trials that recruited patients within 1 week of stroke onset and were published before the end of 2001 were identified from the Cochrane Library and other bibliographic databases. Information on the SSC and outcome event rates was collected for each trial. RESULTS: Of 189 identified trial reports, 57 (30%) reported > or =1 components of the SSC, phase II 14/129 (11%) versus phase III 43/60 (72%) (P<0.001), with 32 (56%) giving all the required parameters. Significance (alpha) was mentioned in 54 (96%) reports; 53 used a significance level of alpha=0.05. And 55 (98%) reports gave the power (1-beta) of the study (median [25th and 75th percentile] 0.80 [0.80, 0.90]). The anticipated percentage of control subjects having a primary outcome event was given in 24 (42%) articles: case fatality 21.8% (11.8%, 23.5%, n=4) and combined death or disability/dependency 55.5% (44.5%, 66.3%, n=20); 25 studies used other outcomes and 8 studies gave insufficient information. Four of the 22 trials achieved a control rate within 5% of their prediction. 49 (86%) reports gave the anticipated treatment effect; case fatality: anticipated 9.5% (1.1%, 12.5%, n=6), achieved -0.3% (-4.1%, +2.4%); combined death or disability/dependency: anticipated 13.0% (10.0%, 16.0%, n=25), achieved 1.8% (-0.5%, +5.4%). The median calculated sample size was 600 (198, 995, n=54). CONCLUSIONS: Too few trial publications report the assumptions underlying their SSC. Most trials were underpowered, ie, power <0.90, used inappropriate assumptions for event rates, and were grossly overoptimistic in their expectation of treatment effect. These deficiencies will together have resulted in trials being far too small and reduced their chance of being able to detect real treatment effects.

Algorithms↗
PubMed2006

[Relationship between sample size and variation of means for personal noise exposure in weaving workers].

OBJECTIVE: To explore the relationship between sample size and variance of means for personal noise exposure in weaving workers as to contributing evidence for establishing personal noise exposure measurement guideline. METHODS: A personal noise exposure measurement database from a group of weaving workers was used in the randomized re-sampling data analysis. The sampling cases were one number selecting from one to fifteen at each randomized re-sampling procedure. The randomized re-sampling was one thousand times from original personal noise exposure measurement database to get one thousands of re-sampling database. One thousands of L(Aeq.8 h) mean were calculated by re-sampling databases. The variation of randomized re-sampling means was analyzed for different re-sampling numbers. RESULTS: The change for narrow trend of maximum, minimum, 95 percent number, 5 percent number of L(Aeq.8 h) mean was faster when randomized re-sampling number was smaller in variation vs randomized re-sampling number curve analysis. After that, the change for narrow trend of L(Aeq.8 h) mean was smooth for increasing the randomized re-sampling numbers. The 95% - 5% of L(Aeq.8 h) mean was about half for randomized re-sampling four cases (3.30 dB) vs one case (7.40 dB), and about one third for seven cases (2.44 dB), and about one fourth for eleven cases (1.85 dB). CONCLUSION: The sample size in personal noise exposure measurement guideline could be selected from four to eleven.

Humans↗
PubMedDate not supplied

Sample size calculations for rescreening cytologic smears.

OBJECTIVE: To describe a method of calculating sample size if rescreening of cytologic material becomes necessary for legal or other reasons. The number of specimens to be reexamined must be large enough to provide adequate confidence in the results and small enough to minimize the cost of investigation. CONCLUSION: Except under very unusual conditions, the sample size is larger than generally thought.

Cell Biology↗
PubMed1998

On the influence of sample size on the prognostic accuracy and reproducibility of renal transplant biopsy.

INTRODUCTION: The minimal specimen size necessary for accurate interpretation of a renal biopsy has not been identified. We attempted such a determination by three different analyses of a collection of biopsies performed in renal transplants. METHODS: First, we studied the influence of three lesions (glomerulosclerosis, arteriolar hyalinosis, interstitial fibrosis/tubular atrophy) in 199 baseline biopsies, obtained at time of transplantation, on transplant outcome. Secondly, we compared the results from the three lesions in baseline biopsy with those from 114 subsequent core biopsies in the same patients. Thirdly, we compared the two baseline biopsies obtained in 118 paired kidneys in cadaver transplantation where both kidneys were used. RESULTS: For statistically significant prediction of outcome from glomerulosclerosis, we found that a specimen containing at least 25 glomeruli was needed in the baseline biopsy. Arteriolar hyalinosis predicted outcome independent of sample size, but became less important than percentage glomerulosclerosis in predicting outcome if only samples containing more than 25 glomeruli were considered. Interstitial fibrosis/tubular atrophy did not predict the outcome of a kidney, independent of sample size. When comparing baseline with subsequent core biopsies, or with paired baseline biopsies, at least 14 glomeruli were necessary to allow even moderate reproducibility of glomerulosclerosis (Cohen's kappa > 0.25) and to allow statistical significance (P < 0.05). The reproducibility of arteriolar hyalinosis was not dependent on sample size but was reproducible in 80% of paired baseline biopsies, and in 67% of the comparison of the baseline with core biopsy. Both precision and significance was lost if sample numbers were reduced by including only larger samples. There was no reproducibility in any study of interstitial fibrosis/tubular atrophy when comparing either baseline with subsequent biopsy, or paired baseline biopsies. SUMMARY: Much larger biopsy samples are necessary than has generally been assumed in order for glomerulosclerosis rates to be reproducible or predictive of outcome. Arteriolar hyalinosis is prognostically important and shows good reproducibility independent of sample size. Interstitial fibrosis/tubular atrophy appear useless as predictors, being of no prognostic importance and lacking reproducibility. Our finding clarifies some of the discrepancies found by different investigators regarding the importance of renal biopsy in predicting prognosis. Preliminary, our data indicate that samples containing fewer than 25 glomeruli are unreliable in determining outcome based on glomerulosclerosis. The importance of our findings which are based only on chronic lesions, with respect to acute changes, is unknown.

Adolescent↗
PubMed2002

Sample size determination.

Scientists who use animals in research must justify the number of animals to be used, and committees that review proposals to use animals in research must review this justification to ensure the appropriateness of the number of animals to be used. This article discusses when the number of animals to be used can best be estimated from previous experience and when a simple power and sample size calculation should be performed. Even complicated experimental designs requiring sophisticated statistical models for analysis can usually be simplified to a single key or critical question so that simple formulae can be used to estimate the required sample size. Approaches to sample size estimation for various types of hypotheses are described, and equations are provided in the Appendix. Several web sites are cited for more information and for performing actual calculations

Animals↗
PubMed1992

Components of blood pressure variability in the elderly and effects on sample size calculations for clinical trials.

This study investigated components of blood pressure variability in the elderly using both ambulatory blood pressure monitoring (ABPM) and casual clinic blood pressure measurement. These were then used to determine sample size requirements for clinical trials of different design scenarios in the elderly. Twenty-six elderly subjects not receiving antihypertensive medication were recruited from general practices and seen on four occasions at weekly intervals. On each occasion of blood pressure was measured in the clinic using a standard mercury sphygmomanometer and then for 24 h using a noninvasive ambulatory monitoring device. The between subject and between subject/within occasion components of blood pressure variability were determined by analysis of variance and used to calculate to sample size requirements for parallel and crossover trials respectively. The between subject variance of mean blood pressure was 1/3 greater with clinic readings, except within a subgroup of subjects who had isolated systolic hypertension (ISH). Increasing the number of readings or occasions on which measurement was performed in a parallel group trial only reduced the variability substantially when the number of subjects involved was small. With crossover designs, the between subject component of variance is eliminated resulting in substantial reduction in sample size. Whereas 60 subjects with ISH would be required to detect a 10 mm Hg difference in systolic blood pressure between two treatments in a parallel design using casual readings, only 18 are required with a crossover trial. If ABPM is used the number of subjects required are 54 and 14, respectively. Reducing variability with ABPM involves a trade-off between the increased number of readings available with the technique against the highly uniform and standardized conditions used to determine clinic blood pressures. ABPM appears most useful as a strategy for reducing sample size in parallel group trials involving small numbers of subjects measured on one occasion.

Aged↗
PubMed2006

The effect of sample size on the assessment of stuttering severity.

The relationships between the length of the speech sample and the resulting disfluency data in 20 stuttering children who exhibited a wide range of disfluency levels were investigated. Specifically, the study examined whether the relative number of stuttering-like disfluencies (SLD) per 100 syllables, as well as the length of disfluencies (number of iterations per disfluent event), varied systematically across 4 consecutive, 300-syllable sections in the same speech sample. The difference in the number of SLD per 100 syllables between the early and later sections of the speech sample was statistically significant. In addition, the length of the speech sample had a critical influence on the identification of stuttering in children exhibiting relatively low levels of disfluency. Also, when a 20% difference in the number of SLD per 100 syllables was taken as a criterion, 50% of the children exhibited upward shifts in continuous speech samples that were longer than 300 syllables (i.e., 600, 900, and 1,200 syllables). Results indicated that, in general, group means for SLD grew larger as the sample size increased. The length of disfluent events did not significantly differ as the sample size increased; however, there were large differences for some children. Implications for clinicians and investigators are discussed.

Child, Preschool↗
PubMed2005

Modified exact sample size for a binomial proportion with special emphasis on diagnostic test parameter estimation.

The design of epidemiologic studies for the validation of diagnostic tests necessitates accurate sample size calculations to allow for the estimation of diagnostic sensitivity and specificity within a specified level of precision and with the desired level of confidence. Confidence intervals based on the normal approximation to the binomial do not achieve the specified coverage when the proportion is close to 1. A sample size algorithm based on the exact mid-P method of confidence interval estimation was developed to address the limitations of normal approximation methods. This algorithm resulted in sample sizes that achieved the appropriate confidence interval width even in situations when normal approximation methods performed poorly.

Algorithms↗
PubMed1989

Cytomorphometry. A methodologic study of preparation techniques, selection methods and sample sizes.

The influence of methodologic aspects on cytomorphometric features was studied using preparations of hepatoma and/or mastocytoma cells. First, two preparation techniques (smear and oese) were compared. Second, four methods of selecting cells for cytomorphometric analysis (two conventional and two stratified methods) were tested for reproducibility. Third, heterogeneous cell populations were used to estimate the required sample size using the running coefficient of variation (CV), and the results were compared with expected (theoretical) values of the required sample size calculated using the standard error of the mean. The results showed significantly lower CVs for the smear preparation technique. The stratified methods appeared to be superior to the conventional methods for selecting cells for measurement. The experimentally assessed sample sizes were considerably lower than the corresponding theoretical calculations. These findings suggest that morphometric assessments in cytologic smears should utilize a stratified cell selection method. While experimentally assessed sample sizes are relatively small and therefore better routinely applicable, they may yield less reliable results in some cases. The need to test a sample for its reproducibility as well as its discriminatory power is emphasized.

Animals↗
PubMed1998

Sample size in clinical trials with dichotomous endpoints: use of covariables.

In many clinical trials, the primary endpoint is dichotomous. In this article, we examine the possibility of reducing the required sample size by removing variation associated with baseline covariables. Three measures are used to study the size of the reduction. Simulation studies based on a database of head trauma and of stroke patients suggested that a substantial reduction in the sample size can be achieved when the correlation between the endpoint and covariables is strong. A simple ad hoc formula for approximating the required sample size is proposed.

Adult↗
PubMed1992

Quantitative motor unit analysis: the effect of sample size.

This study of quantitative electromyography examines the influence of sample size on motor unit action potential (MUAP) tolerance limits, intertrial variability, and diagnostic sensitivity. We recorded 20 randomly selected MUAPs from the biceps muscle twice in 21 normal subjects, and once in 10 patients with myopathy. The 95% tolerance limits for mean total duration in normal subjects progressively narrowed from 6.6 to 14.2 ms for 5 MUAPs to 7.4 to 13.0 ms for 20 MUAPs. The 95% tolerance limits for intertrial variability were +/-22% for mean total duration of 20 MUAPs. Larger sample size had a greater effect on reducing intertrial variability than on narrowing 95% tolerance limits for amplitude and area. Quantitative EMG results for duration supported the presence of myopathy in 2 of 10 patients with analysis of 5 MUAPs, and 9 patients with analysis of 20 MUAPs. Although analysis of 5 potentials may be adequate for diagnosis occasionally, quantitative analysis of 20 MUAPs narrows tolerance limits, reduces intertrial variability, and improves diagnostic sensitivity.

Action Potentials↗
PubMed1991

Rheumatoid arthritis antirheumatic drug trials. II. Tables for calculating sample size for clinical trials of antirheumatic drugs.

The calculation of sample size requires knowledge of the standard deviation (SD) of index variables. Unfortunately, there are no published lists of SD and it is exceedingly difficult to locate variance estimates based on relevant populations. We used standardized procedures to determine in 60 patients with rheumatoid arthritis (RA) the SD of key outcome measures recommended in current Food and Drug Administration and European League Against Rheumatism guidelines for RA clinical trials. We anticipate that these tables will be useful to clinical researchers in selecting outcome measures as well as for calculating sample size requirements for future clinical studies in RA.

Anti-Inflammatory Agents↗
PubMed2002

Determination of minimum sample size and discriminatory expression patterns in microarray data.

MOTIVATION: Transcriptional profiling using microarrays can reveal important information about cellular and tissue expression phenotypes, but these measurements are costly and time consuming. Additionally, tissue sample availability poses further constraints on the number of arrays that can be analyzed in connection with a particular disease or state of interest. It is therefore important to provide a method for the determination of the minimum number of microarrays required to separate, with statistical reliability, distinct disease states or other physiological differences. RESULTS: Power analysis was applied to estimate the minimum sample size required for two-class and multi-class discrimination. The power analysis algorithm calculates the appropriate sample size for discrimination of phenotypic subtypes in a reduced dimensional space obtained by Fisher discriminant analysis (FDA). This approach was tested by applying the algorithm to existing data sets for estimation of the minimum sample size required for drawing certain conclusions on multi-class distinction with statistical reliability. It was confirmed that when the minimum number of samples estimated from power analysis is used, group means in the FDA discrimination space are statistically different. CONTACT: gregstep@mit.edu

Acute Disease↗
PubMed1989

Methods of determining sample sizes in clinical trials.

A problem of great interest and implication to a medical researcher planning an investigation is the determination of sample size. This should be decided by balancing statistical against practical and clinical considerations. Unfortunately, many give little thought to sample size and choose an arbitrary number (20, 50, 100, etc.) for their study. This paper provides an understanding of the basis for determining the sample size and some helpful tools.

Child↗
PubMed1999

A modification of Simon's optimal design for phase II trials when the criterion is median sample size.

We present a modification to Simon's optimal design for phase II trials in which the objective is to minimize the median sample size rather than the expected sample size when the true response rate is poor (p = p0). We argue that the modified design may be preferred in smaller institutions when the focus is on a single or small number of phase II trials rather than a large program of phase II trials.

Algorithms↗
PubMed2003

Sample size for collecting germplasms--a polyploid model with mixed mating system.

The present paper discusses a general expression for determining the minimum sample size (plants) for a given number of seeds or vice versa for capturing multiple allelic diversity. The model considers sampling from a large 2 k-ploid population under a broad range of mating systems. Numerous expressions/results developed for germplasm collection/regeneration for diploid populations by earlier workers can be directly deduced from our general expression by assigning appropriate values of the corresponding parameters. A seed factor which influences the plant sample size has also been isolated to aid the collectors in selecting the appropriate combination of number of plants and seeds per plant. When genotypic multiplicity of seeds is taken into consideration, a sample size of even less than 172 plants can conserve diversity of 20 alleles from 50,000 polymorphic loci with a very large probability of conservation (0.9999) in most of the cases.

Alleles↗
PubMed2006

Considerations on the sample size of wood mice used to biomonitor metals.

The concentrations of various metals (Zn, Cu, Mn and Cr) in liver, kidneys and brain from specimens of the wood mouse Apodemus sylvaticus captured from 5 sites were measured. Two of the sites were in a restored mine dump, another in an area characterized by serpentized soils and the remaining two were control sites. The sample size required for statistical differentiation of the sampling sites was calculated from the mean values and the variability in bioaccumulation corresponding to each of the sites. The relationship between the sample size and the results of the statistical test used to reveal significant differences between the mean concentrations of metals in organs from A. sylvaticus is demonstrated. The homeostatic control exerted by the wood mice on the tissue levels of metals reduced the interpopulational variability, thereby homogenizing the mean bioaccumulation corresponding to the different sampling stations. The sample size, tissue regulation of the levels of heavy metals and the patterns of variability are of vital importance in evaluating the usefulness of A. sylvaticus as a biomonitor of heavy metals.

Animals↗
PubMed1981

Introduction to sample size determination and power analysis for clinical trials.

The importance of sample size evaluation in clinical trials is reviewed and a general method is presented from which specific equations are derived for sample size determination or the analysis of power for a wide variety os statistical procedures. The method is discussed and illustrated in relation to the t test, tests for proportions, tests of survival time, and tests for correlations as they commonly occur in clinical trials. Most of the specific equations reduce to a simple general form for which tables are presented.

Clinical Trials as Topic↗