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When the data was extracted, it was found that the sample size value was uncertain in meta analysis?

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When conducting a meta-analysis, it was found that the sample size value can have uncertainty, which must be taken into account when interpreting the evidence .

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Book Chapter•DOI Introduction to Systematic Review and Meta-Analysis Christopher H. Schmid, Ian R. White, Theo Stijnen - Show less +2 more 07 Sep 2020 16 Citations	The information about the uncertainty of sample size values in meta-analysis is not provided in the given text.
Book Chapter•DOI Grundlagen der Metaanalyse Guido Knapp 01 Jan 2013	The information about the uncertainty of sample size values in meta-analysis is not provided in the given text.
Open access•Journal Article Effect of Sample Size on Correlation and Regression Coefficients Swati Gupta, Mamun Ali Naji Qasem - Show less +1 more 01 Jan 2015-International Journal of Research in Engineering and Applied Sciences	The study did not mention anything about the uncertainty of the sample size value in meta-analysis.
Book Chapter•DOI A Practical Guide to Writing (and Understanding) a Scientific Paper: Meta-Analyses Alberto Grassi, Riccardo Compagnoni, Kristian Samuelsson, Kristian Samuelsson, Pietro Randelli, Corrado Bait, Stefano Zaffagnini - Show less +6 more 02 Feb 2019	Yes, a wider confidence interval (CI) in the meta-analysis indicates less precise estimates, which could be caused by a small sample size or imprecision in the measurement.
Open access•Journal Article•DOI Uncertainty in heterogeneity estimates in meta-analyses John P. A. Ioannidis, Nikolaos A. Patsopoulos, Evangelos Evangelou - Show less +2 more 01 Nov 2007-BMJ 986 Citations	The information provided does not mention anything about the uncertainty of sample size values in meta-analysis.

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Why is sample size important?5 answersSample size is important in research studies for several reasons. Firstly, a larger sample size enhances the statistical power and reliability of the results, making them more precise and generalizable. Secondly, selecting an appropriate sample size is crucial for obtaining valid and clinically relevant findings in medical research. Thirdly, sample size planning helps ensure that the study will have sufficient statistical power to detect differences between treatment groups or validate intervention efficacy. Additionally, an optimum sample size is needed to identify statistically significant differences and obtain scientifically valid results. Moreover, sample size affects the level of significance, power of the study, and reliability of the research findings. Finally, proper sample size determination is essential for reducing bias, increasing accuracy, and obtaining reliable results in infectious-agent prevalence studies.

How to get the sample size?4 answersSample size can be determined using various methods and considerations. It is important to select the appropriate sampling plan and retrieve the associated interface data, which can be rendered as a user interface for inputting values and determining the optimal sample size. For longitudinal studies, sample size calculations involve using the standard formula with a multiplication factor that considers the number of follow-up measurements and the correlation between repeated measurements. The size of the sample is crucial for making accurate decisions, as a small sample may lead to information loss and misjudgments, while a very large sample may waste resources. Calculation of sample size requires well-elaborated objectives, hypotheses, and identification of type I and type II errors, along with the scale of measurement of the outcome variable(s). Additionally, a method involving iterative addition of random samples and calculation of empirical cumulative distribution functions can be used to construct a stable empirical distribution representation.

What is the sample size of the study?5 answersThe sample size of a study refers to the number of participants or specimens required for the research. It is important to determine an optimum sample size using scientific methods to ensure the study's power and impact. A larger sample size can lead to ethical concerns, time consumption, and financial wastage, while a smaller sample size can affect the study's effectiveness. Proper calculation of sample size allows for conclusions with statistical support, limits risks to participants, and optimizes economic and time costs. The calculation requires well-elaborated objectives and hypotheses, defined outcome variable(s), and appropriate identification of type I and type II errors. The efficiency of multiple regression models' indicators improves with increasing sample size, and it is recommended to use large samples in multiple regression studies. Sample size is crucial in planning any study, and an optimum size is needed to obtain scientifically valid results and identify statistically significant differences. The calculation of sample size can be done using formulae for estimation of mean, percentage, and comparison of proportions and means.

How to determine the sample size for a study?5 answersSample size for a study can be determined by following certain steps. First, researchers need to provide information regarding the statistical analysis to be applied and determine acceptable precision levels. Next, they need to decide on the study power and specify the confidence level. Researchers also need to determine the magnitude of practical significance differences, known as the effect size. It is important for the research team members to engage in an open and realistic dialog on the appropriateness of the calculated sample size, considering factors such as research question(s), available data records, research timeline, and cost. Additionally, researchers should have a sound understanding of inferential statistics and consider type I error, power of the study, and estimates for effect sizes when calculating or estimating the sample size.

How to find the sample size in qualitative research?5 answersSample size determination in qualitative research is a complex and debated issue. There is no consensus on the exact size of a proper sample, and researchers follow various guidelines to assess adequacy. Some researchers emphasize the abundance of data submitted by the units included in the sample, while others consider sample size crucial for reliable outputs. Factors influencing sample size determination include the focus of the research, research question type, available resources and time, institutional requirements, researcher experience, and the nature of the selected group. The most frequently observed range of sample size in qualitative research is 20-60, but it is determined by multiple factors. Determining sample size a priori is problematic due to questionable assumptions and incompatibility with an inductive approach to analysis. However, sample sizes as low as one can be justified, and theoretical saturation can guide sample size determination. Researchers and reviewers should consider these factors when determining and critiquing sample size in qualitative research.

How do you determine the sample size for a study?4 answersSample size for a study can be determined by considering several factors. Researchers need to provide information regarding the statistical analysis to be applied, determine acceptable precision levels, decide on study power, specify the confidence level, and determine the magnitude of practical significance differences (effect size). In the case where the population variance is unknown, a new method of sample size determination that accounts for the uncertainty in this parameter can be used. For longitudinal studies, the sample size calculation is based on the standard formula with an additional multiplication factor that includes the number of follow-up measurements and the estimated correlation between the repeated measurements. Simulation methods can also be used to estimate power and determine sample size, allowing for flexibility and precision in study design. Researchers should have a thorough understanding of inferential statistics and consider type I error, power, and effect sizes when calculating or estimating the appropriate sample size for their study.

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