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A method is presented to obtain sample sizes for cases and controls that are required to provide approximate confidence intervals on the log odds ratio of predetermined width 2d and probability of coverage as a function of assumed exposure rates in the control group, assumed odds ratio psi, required d, and ratio C:1 of controls to cases.
This study describes a new method of quantifying anteriorly located cortical cataracts using retroillumination photographs and computer planimetry. Cortical cataracts were graded clinically and then photographed using the Neitz retroillumination camera twice by each of 2 photographers. The cataract outlines were traced onto a transparent overlay, and computer planimetry was performed using a Scan Maker 600ZS, a MAC II Computer and specially developed software. We estimated the measurement error of the method and its associated effect on sample size estimates for clinical studies. We calculated that the variability in this technique would contribute about 21 additional subjects to overall sample size estimates in studies comparing the mean areas of cortical opacities. In many studies this would be a small addition to total sample size requirements. This technique provides clinically useful measurements of the size of a cortical opacity as seen on a retroillumination photograph. This may be useful for future clinical studies on natural progression of cortical cataracts as well as for clinical trials of anticataract drugs.
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.
Because of their larger study populations and longer durations, prevention trials typically are more costly than treatment trials. Thus it is important to analyze costs systematically to aid in making cost-effective decisions during the conduct of prevention trials as well as in the original design. Cost analysis must be tied to sample size estimation because costs depend on such factors as the total number of person-years of follow-up and the number of trial outcomes, which are not basic design parameters but are derived quantities resulting from sample size estimation. We illustrate the use of cost analysis to decide among options for future conduct of an ongoing prevention trial with three issues that have arisen during the Carotene and Retinol Efficacy Trial (CARET): the trade-off between extending the duration of the trial or increasing the number of participants, the effect on costs of delay in accrual, and the cost effectiveness of particular retention activities.
Although sample size calculation is mandatory in clinical trials, the power of most of the published small size clinical studies, was only about 0.25 instead of 0.80 which is normally required in a standard randomized controlled trial. This phenomenon is probably due to the publication bias. In a cancer clinical study, the ideal sample size needed in a trial exceeds over a thousand, when significance level was fixed under 0.05 and treatment difference is estimated from 10 to 15%. In such cases, evaluation of a new treatment in less common cancers or in a specified strata become unfeasible. Although statistically plausible clinical trial is difficult, small trials of newly advocated treatment is likely to be performed elsewhere, and presentation of these haphazard results might propagate a wrong information about the new treatment. To prevent the dissemination of these biased results, 1) preregistration of all planned clinical trials to an authorized organization before the initiation of the trial, 2) randomization of the patients entered in the trial from the first case, and 3) registration of all available data of the patients and meta-analysis of preregistered multiple trials, should be the most effective counterplans. In order to achieve those functions, installation of a computer assisted coordinating center is considered to be the best solution for the proper evaluation of the clinical trial as well as for the evaluation of a new treatment. With the collaboration of regional affiliating hospitals, a pilot study have started to establish a computer network system.
The errors inherent in EM autoradiography are discussed and certain of them deemed to be of particular practical significance in the quantitative assessment of preparations. A method is described for estimating the standard errors attributable to each of several sources of variation and thence for obtaining the overall standard error value to be attached to relative activity estimates obtained in the method of Downs & Williams (1978). In an appendix, a fully worked example is given illustrating clearly the strategy of the method and the magnitudes of error estimates that are to be attached to the final specific activity values.
To estimate vaccine protective efficacy, defined as VE = 1 - ARV/ARU where ARV is the disease attack rate in the vaccinated group and ARU is the disease attack rate in the controls, investigators have used both cohort and case-control designs. For each design, we present a method for calculation of the sample size required to provide an approximate confidence interval for VE of predetermined width and probability of coverage. The required sample size is a function of the desired width of the confidence interval, the probability of coverage, the assumed VE, and, for cohort designs, the assumed disease attack rate in the controls, and for case-control designs, the assumed vaccine exposure prevalence for the controls.
Fifty-four patients with chronic stable angina were studied to determine and compare weekly variability of indexes for the detection of myocardial ischemia. All patients underwent three single-blind placebo periods, each lasting 1 week. An exercise treadmill test, 24 h ambulatory electrocardiographic (Holter) monitoring (analyzed blindly) and an accurate diary of anginal attacks and nitroglycerin use were obtained at the end of each placebo period. An unbalanced, completely random component of variance analysis was used to calculate a component for within subject variability and a component for among subject variability. The coefficient of variation and percent variation (within subjects) of onset of chest pain during exercise were 19% and 30%, respectively; the corresponding values were 28% and 33% for onset of 1 mm ST depression, 15% and 15% for exercise duration, 44% and 27% for number of ischemic episodes/24 h, 56% and 43% for anginal frequency and 55% and 27% for nitroglycerin consumption, respectively. With use of this statistical method and variation within subjects, the change in the value of each variable necessary to exceed those attributable to spontaneous variation was determined. The trade-off between repeated measurements and number of subjects, the sample size estimated for planning studies and the minimal sample size for using various designs were also determined. Although the data indicate that all indexes for myocardial ischemia, both during exercise and during daily activity, vary considerably, but the exercise variables have less variability and are more reproducible.(ABSTRACT TRUNCATED AT 250 WORDS)
The prevalence of a variety of risk factors and their strength of association with a disease can vary greatly among apparently similar communities. In small communities, risk estimates can also vary from year to year. An identification of important risk factors in each community is then needed, so that interventions can be specifically oriented towards the needs of each specific community. The attributable risk is the adequate measure of association for these purposes. The purpose of this paper is to determine the minimum sample size required to detect a given attributable risk in cross-sectional studies. A table was constructed, presenting the number of exposed subjects necessary to detect a given attributable risk for different combinations of prevalence of disease and prevalence of exposure to a given risk factor, with a power of 0.80 and alpha of 0.05.
General guidelines are presented for the use of cluster-sample surveys for health surveys in developing countries. The emphasis is on methods which can be used by practitioners with little statistical expertise and no background in sampling. A simple self-weighting design is used, based on that used by the World Health Organization's Expanded Programme on Immunization (EPI). Topics covered include sample design, methods of random selection of areas and households, sample-size calculation and the estimation of proportions, ratios and means with standard errors appropriate to the design. Extensions are discussed, including stratification and multiple stages of selection. Particular attention is paid to allowing for the structure of the survey in estimating sample size, using the design effect and the rate of homogeneity. Guidance is given on possible values for these parameters. A spreadsheet is included for the calculation of standard errors.
Twenty-six eyes with posterior subcapsular opacities of various sizes were photographed with the Neitz-Kawara Retroillumination camera. The outline of the opacity in a single photograph of each opacity was traced onto a transparent plastic overlay twice by two independent outliners. Two methods were used to estimate the area within the outlines of the opacities. In the first, a transparent overlay with a standard grid was used to count the number of boxes within the outlines. The second method used computer planimetry to estimate the area within the tracings. We estimated the measurement error associated with a single outlining of an opacity and the contribution of the measurement error to overall sample size requirements in studies comparing the mean areas of posterior subcapsular opacities. Variability in the measurement techniques contributed fewer than 20 additional subjects to overall sample size estimates, a small contribution to total sample size requirements in most studies. An outliner's inherent variability in outlining an opacity was a much larger contributor to the measurement error than was variability in assessing the area of the outline of the opacity. While within outliner variability was similar for the two persons outlining the opacities, there were systematic differences in the way the two traced the outlines. Variability from the use of separate photographs of the same opacity taken by different photographers was minimal.
Prospective population studies have established that fibrinogen is an independent predictor for ischemic heart disease and stroke. These study conclusions have prompted recommendations that fibrinogen determinations be included in the cardiovascular risk profile. The routine availability of fibrinogen measurements may result in widespread screening prior to establishing the validity of a single fibrinogen level as an accurate descriptor for individual subjects. The objectives of this study were to describe the methodological and intraindividual components of variability in fibrinogen measurements determined by using the Clauss method; to establish the usefulness of a single fibrinogen measurement on risk stratification and retest reproducibility; and to determine the influence of intraindividual fibrinogen variability on sample size estimates. Fibrinogen levels were measured by a modification of the Clauss method. Three cohorts of apparently healthy, nonsmoking volunteers were recruited. The single-day intra-individual component of fibrinogen variability was determined in 39 subjects. For the 5-day intraindividual component of fibrinogen variability, 32 subjects were recruited, and in the 6-week intraindividual study, 28 subjects were included. The coefficient of variation for the methodological component of fibrinogen variability was 5.8% as determined from batch analyses, but the intraindividual coefficient of variation for replicate measures on a single day was 10.7%. The 5-day intraindividual coefficient of variation was 14.2%, and for the 6-week period it was 17.8%. Based on the 6-week data, an average of four fibrinogen measures is required to reduce misclassification error to less than 10%. Sample size estimates were made based on predetermined levels of statistical power and the 6-week intraindividual and interindividual variability estimates.(ABSTRACT TRUNCATED AT 250 WORDS)
In planning case-control studies with matched sets, the calculation of exact sample sizes is difficult, because this calculation depends on some nuisance parameters that are usually unknown in practice. Using the Pitman efficiency of Miettinen's test relative to McNemar's test, Schlesselman and Stolley (Case-control studies: design, conduct, analysis. Oxford: Oxford University Press, 1982:144-70) derived an approximate sample size formula which requires the assumption that the difference in exposure rates between cases and controls is small. Furthermore, on the basis of an assumption similar to that used in Schlesselman and Stolley's approach, Taylor (Stat Med 1986;5:29-36) proposed another approximation formula. In this paper, an alternative and explicit formula that does not require the exposure difference to be small between case and control groups has been derived. Monte Carlo studies are given for comparing the accuracy of these three procedures. The results indicate that when odds ratios of exposure between cases and controls are small (less than or equal to 4) and there is more than one matched control per case, the formula derived in this paper seems to be the best. When odds ratios are large (greater than or equal to 5), however, Taylor's more conservative estimate is recommended, unless the exposure prevalence in the general population is large (0.9).
While most epidemiologic cohort studies are preceded by some sort of feasibility study, details of such prior investigations are rarely reported. Yet it is during such feasibility studies that critical decisions are made, such as site selection and definition of exposure. Here we present the details on one such feasibility study, conducted to determine the possibility of a cohort mortality study of workers exposed to ethylene oxide. Issues discussed include methods for estimating sample size and power, for estimating levels of exposure, and for assessing the adequacy of personnel records.
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The prevalence of vitamin A deficiency among two to ten years old children in a rural area of Mali was assessed by ophthalmic examination, determination of plasma retinol levels and impression cytology with transfer tests. A Public Health problem of vitamin A deficiency was identified in this rural area by: the prevalence of nightblindness significantly (p < 0.001) above the cut-off (1%) defined by the World Health Organization (WHO); the prevalence of corneal scarring significantly (p < 0.001) above the WHO's cut-off (0.05%); the percentage of subjects with plasma retinol levels below 0.35 mumol/l (10 micrograms/dl) significantly (p < 0.001) higher than the WHO's threshold (5%); and 52.8 +/- 8.2% children with "Abnormal" impression cytology as determined by the impression cytology test (IC). This preliminary survey confirmed widespread vitamin A deficiency in Mali. The minimum sample size required for a study using the impression cytology test to determinate a Public Health problem in a population was calculated for different situations. Ophthalmic examination indicated a very high rate of active trachoma (29.6 +/- 7.0%), and a relationship between active trachoma and impression cytology results was identified.
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