Assessing sample size and variable number in multivariate data, with specific reference to cone morphology variation in a population of Picea sitchensis

1985 ◽  
Vol 63 (2) ◽  
pp. 232-241 ◽  
Author(s):  
Rob Scagel ◽  
Y. A. El-Kassaby ◽  
J. Emanuel
Keyword(s):  
Sample Size ◽  
Multivariate Data ◽  
Variable Number ◽  
Picea Sitchensis ◽  
Interindividual Variation ◽  
Specific Reference ◽  
Size Estimation ◽  
Pilot Studies ◽  
Nested Models ◽  
Cone Morphology

A multivariate extension of univariate sample size estimation is outlined that enables one to determine sample size for a multivariate study. The procedure is presented and illustrated by application to intraindividual and interindividual variation of cone morphology in a population of Picea sitchensis (Bong.) Carr. The method involves the stabilization of a scalar estimate of the structure of the correlation matrix (the determinant) among variables for a given sample size. The sample-specific dependency of previously described methods is avoided by random selection of several replicates in nonstructured and structured (nested) models. The procedure is best applied in pilot studies where it can aid in the characterization of multivariate data prior to analysis. Additionally, repeatability estimates for cone scale morphology are presented.

scholarly journals Design, analysis, and reporting of pilot studies in HIV: a systematic review and methodological study

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Hussein Ali El-Khechen ◽  
Mohammed Inam Ullah Khan ◽  
Selvin Leenus ◽  
Oluwatobi Olaiya ◽  
Zoha Durrani ◽  
...  
Keyword(s):  
Qualitative Methods ◽  
Sample Size ◽  
Contextual Information ◽  
Primary Objective ◽  
People Living With Hiv ◽  
Size Estimation ◽  
Methodological Study ◽  
Pilot Studies ◽  
Hiv Research ◽  
Living With Hiv

Abstract Background Pilot studies are essential in determining if a larger study is feasible. This is especially true when targeting populations that experience stigma and may be difficult to include in research, such as people with HIV. We sought to describe how pilot studies have been used to inform HIV clinical trials. Methods We conducted a methodological study of pilot studies of interventions in people living with HIV published until November 25, 2020, using Medline, Embase, and Cochrane Controlled Register of Trials (CENTRAL). We extracted data on their nomenclature, primary objective, use of progression criteria, sample size, use of qualitative methods, and other contextual information (region, income, level, type of intervention, study design). Results Our search retrieved 10,597 studies, of which 248 were eligible. The number of pilot studies increased steadily over time. We found that 179 studies (72.2%) used the terms “pilot” or “feasibility” in their title, 65.3% tested feasibility as a primary objective, only 2% used progression criteria, 23.9% provided a sample size estimation and only 30.2% used qualitative methods. Conclusions Pilot studies are increasingly being used to inform HIV research. However, the titles and objectives are not always consistent with piloting. The design and reporting of pilot studies in HIV could be improved.

scholarly journals A systematic review of the quality of conduct and reporting of survival analyses of tuberculosis outcomes in Africa

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Moses M. Ngari ◽  
Susanne Schmitz ◽  
Christopher Maronga ◽  
Lazarus K. Mramba ◽  
Michel Vaillant
Keyword(s):  
Systematic Review ◽  
Sample Size ◽  
Survival Function ◽  
Sample Size Estimation ◽  
Size Estimation ◽  
Survival Curves ◽  
Survival Analyses ◽  
Survival Regression

Abstract Background Survival analyses methods (SAMs) are central to analysing time-to-event outcomes. Appropriate application and reporting of such methods are important to ensure correct interpretation of the data. In this study, we systematically review the application and reporting of SAMs in studies of tuberculosis (TB) patients in Africa. It is the first review to assess the application and reporting of SAMs in this context. Methods Systematic review of studies involving TB patients from Africa published between January 2010 and April 2020 in English language. Studies were eligible if they reported use of SAMs. Application and reporting of SAMs were evaluated based on seven author-defined criteria. Results Seventy-six studies were included with patient numbers ranging from 56 to 182,890. Forty-three (57%) studies involved a statistician/epidemiologist. The number of published papers per year applying SAMs increased from two in 2010 to 18 in 2019 (P = 0.004). Sample size estimation was not reported by 67 (88%) studies. A total of 22 (29%) studies did not report summary follow-up time. The survival function was commonly presented using Kaplan-Meier survival curves (n = 51, (67%) studies) and group comparisons were performed using log-rank tests (n = 44, (58%) studies). Sixty seven (91%), 3 (4.1%) and 4 (5.4%) studies reported Cox proportional hazard, competing risk and parametric survival regression models, respectively. A total of 37 (49%) studies had hierarchical clustering, of which 28 (76%) did not adjust for the clustering in the analysis. Reporting was adequate among 4.0, 1.3 and 6.6% studies for sample size estimation, plotting of survival curves and test of survival regression underlying assumptions, respectively. Forty-five (59%), 52 (68%) and 73 (96%) studies adequately reported comparison of survival curves, follow-up time and measures of effect, respectively. Conclusion The quality of reporting survival analyses remains inadequate despite its increasing application. Because similar reporting deficiencies may be common in other diseases in low- and middle-income countries, reporting guidelines, additional training, and more capacity building are needed along with more vigilance by reviewers and journal editors.

scholarly journals Tamaño óptimo de la muestra

2017 ◽  
Vol 5 (9) ◽  
Author(s):  
M. H. Badii ◽  
J. Castillo ◽  
A. Guillen
Keyword(s):  
Sample Size ◽  
Normal Distribution ◽  
Key Words ◽  
Sample Size Estimation ◽  
Size Estimation ◽  
Bias Estimation ◽  
Population Variance ◽  
Population Proportion ◽  
Estimation Process ◽  
The Mean

Key words: Bias, estimation, population, sampleAbstract. The basics of sample size estimation process are described. Assuming the normal distribution, the procedures for estimation of sample size for the mean; with and without knowledge of the population variance, and population proportion are noted. Sample size for more than one population feature is also given.Palabras clave: Estimación, muestra, población, sesgoResumen. Se describen los fundamentos del proceso de la estimación del tamaño óptimo de la muestra. Suponiendo una distribución normal para una población, se notan los procedimientos de la estimación del tamaño óptimo de la muestra para la media muestral con y sin el conocimiento de la varianza poblacional. Se presenta el tamaño óptimo de la muestra con más de una característica poblacional.

Null Hypothesis Significance Testing: Ramifications, Ruminations and Recommendations

2005 ◽  
Vol 35 (1) ◽  
pp. 1-20 ◽  
Author(s):  
G. K. Huysamen
Keyword(s):  
Sample Size ◽  
Confidence Intervals ◽  
Effect Size ◽  
Null Hypothesis ◽  
Significance Testing ◽  
Population Parameter ◽  
Size Estimation ◽  
Null Hypothesis Significance Testing ◽  
Point Estimates ◽  
Size Estimates

Criticisms of traditional null hypothesis significance testing (NHST) became more pronounced during the 1960s and reached a climax during the past decade. Among others, NHST says nothing about the size of the population parameter of interest and its result is influenced by sample size. Estimation of confidence intervals around point estimates of the relevant parameters, model fitting and Bayesian statistics represent some major departures from conventional NHST. Testing non-nil null hypotheses, determining optimal sample size to uncover only substantively meaningful effect sizes and reporting effect-size estimates may be regarded as minor extensions of NHST. Although there seems to be growing support for the estimation of confidence intervals around point estimates of the relevant parameters, it is unlikely that NHST-based procedures will disappear in the near future. In the meantime, it is widely accepted that effect-size estimates should be reported as a mandatory adjunct to conventional NHST results.

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