Hong Kong Baptist University Jiandong Shi

New Developments in Meta-analysis with Five-number Summary by Jiandong Shi

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New Developments in Meta-analysis with Five-number Summary

Author : Jiandong Shi

Publisher : Hong Kong Baptist University

Published : 2021

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Number of Pages : 156 Pages

Language : en

Descriptions New Developments in Meta-analysis with Five-number Summary

Meta-analysis is a statistical method for synthesizing multiple studies to achieve more comprehensive and reliable conclusions. This thesis mainly focuses on the meta-analysis with continuous outcomes, where some studies are reported with the whole or part of the five-number summary including the minimum and maximum values, the first and third quartiles, and the median. Given that most existing meta-analysis models can only handle the studies reported with the sample mean and standard deviation (SD), it is often desired to convert the five-number summary back to the sample mean and SD before synthesis, as otherwise the studies reported with the five-number summary have to be excluded from further analysis. To tackle this problem, some data transformation methods have emerged recently, and they are getting moreand more popular in practice. We note, however, that most popular methods for data transformation are builton the normality assumption, which may not always hold in practice. In particular, when a study chooses to report the five-number summary, it can be an indication thatthe underlying data may not be normal or symmetric. For such data, if still applyingthe normal-based methods for data-transformation, the final results can be misleadingor even wrong in meta-analysis. Motivated by this, we propose to further enhancethe meta-analysis literature on data transformation with the five-number summary. Specifically, this thesis consists of four important projects including (1) the hypothesis tests for skewness and normality, (2) the mean and variance estimation from the five-number summary of a log-normal distribution, (3) new effect size estimation methods, and (4) a new paradox in random-effects meta-analysis. In Chapter 2, we propose three skewness tests and a normality test with thewhole or part of the five-number summary. Despite of the limited data available, the information in the five-number summary, together with the sample size, is surprisingly sufficient enough to conduct the skewness tests. Moreover, when the five-number summary is fully available, we further incorporate the kurtosis information in the test for testing the normality beyond skewness. Simulation studies demonstrate that the type I error rates are well controlled and the newly proposed tests also provide good statistical power. In Chapter 3, we propose to estimate the mean and variance from the reported five-number summary of a log-normal distribution. For normal data, some well-performed methods are established. However, when the data are significantly skewed,there are few methods that could properly handle the problem. Motivated by this and noting that many skewed medical data are modeled with the log-normal distribution, we provide two types of estimators for the mean and variance with the five-number summary of a log-normal distribution. Their performance is demonstrated by the simulation studies and real data analysis. In Chapter 4, we develop new methods that estimate the mean difference and standardized mean difference from the five-number summary. This is motivated by the fact that, even though the normal-based methods can be readily applied, the estimated sample mean and SD are unlikely to be the same as the true values. As a consequence, if one directly applies them as the true sample mean and SD and then applying the classical methods including the Cohen's d or Hedges' g to estimate the effect size, it may yield biased estimates so that the final meta-analytical results can be unreliable. Our new methods, as demonstrated by simulation studies, achieve abetter accuracy and a higher coverage probability than the existing methods. In Chapter 5, we introduce a new paradox in random-effects meta-analysis. Oncethe new paradox appears, the individual studies and the meta-analytical result arecontradictory, which leads to a dilemma for clinical decision making. As found, the key reason for the paradox is the between-study heterogeneity involved in random-effects meta-analysis. In particular when the heterogeneity is large and the number of studies is small in meta-analysis, the probability of the new paradox appearing is notignorable. Moreover, the new paradox only appears in random-effects meta-analysisbut it does not exist in the common-effect and fixed-effects models. It thus raises an interesting question whether the current random-effects model is reasonable andtenable for meta-analysis, or it needs to be abandoned or further improved.

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Results New Developments in Meta-analysis with Five-number Summary

New Developments in Meta-analysis with Five-number Summary - New Developments in Meta-analysis with Five-number Summary. Jiandong SHI; Department of Mathematics; Student thesis: Doctoral Thesis. Date of Award: 27 Sep 2021: Original language: English: Supervisor: ... New Developments in Meta-analysis with Five-number Summary. SHI, J. (Author). 27 Sep 2021

Optimally estimating the sample standard deviation from the five-number - Abstract. When reporting the results of clinical studies, some researchers may choose the five-number summary (including the sample median, the first and third quartiles, and the minimum and maximum values) rather than the sample mean and standard deviation (SD), particularly for skewed data. For these studies, when included in a meta-analysis

Optimally estimating the sample standard deviation from the ﬁve-number - are capable to serve as "rules of thumb" in meta-analysis for studies reported with the ﬁve-number summary. Finally for practical use, an Excel spreadsheet and an online calculator are also provided for implementing our optimal estimators. Key words: Five-number summary, Interquartile range, Range, Sample mean, Sam-ple size, Standard

Five Number Summary | How To Calculate 5 Number Summary - Analytics Vidhya - Five number summary is a part of descriptive statistics and consists of five values and all these values will help us to describe the data. The minimum value (the lowest value) 25th Percentile or Q1. 50th Percentile or Q2 or Median. 75th Percentile or Q3. Maximum Value (the highest value) How to calculate Five Number Summary. Let's understand

Min, Max and the Five-Number Summary - Annenberg Learner - 2 Part B: The Median and the Three-Number Summary (35 Minutes) 3 Part C: Quartiles and the Five-Number Summary (35 minutes) 4 Part D: The Box Plot (25 minutes) 5 Part E: Finding the Five-Number Summary Numerically (30 minutes) 6 Homework; 5 Variation About the Mean

What is a 5 Number Summary? - YouTube - What is a 5 number summary of a set of data? In this math lesson we will go over an example of taking a set of data and finding its 5 number summary, which

How to estimate the sample mean and standard deviation from the five - To conduct meta-analysis for pooling studies, one needs to first estimate the sample mean and standard deviation from the five number summary. A number of studies have been proposed in the recent

Five-Number Summaries and Boxplots - HKT Consultant - The five-number summary indicates that the starting salaries in the sample are between 5710 and 6325 and that the median or middle value is 5905; and, the first and third quartiles show that approximately 50% of the starting salaries are between 5857.5 and 6025. 2. Boxplot. A boxplot is a graphical display of data based on a five-number summary

PDF How to interpret results of meta- analysis - Erasmus Research Institute - The bottom row (or ^summary row) of the forest plot turns the plot into a meta-analysis _. This is the row that represents the result of the meta-analysis. In . Meta-Essentials. this meta-analytic result (line 13 in Figure 1) consists of two intervals, both around the same bullet. This bullet represents the . weighted average effect

How to Calculate the 5-Number Summary for Your Data in Python - The NumPy functions min () and max () can be used to return the smallest and largest values in the data sample; for example: 1. data_min, data_max = (), () We can put all of this together. The example below generates a data sample drawn from a uniform distribution between 0 and 1 and summarizes it using the five-number summary

An overview of meta-analysis for clinicians - PMC - A meta-analysis may yield conclusive results when individual studies are inconclusive. Furthermore, meta-analyses investigate the source of variation and different effects among subgroups. In summary, a meta-analysis is an objective, quantitative method that provides less biased estimates on a specific topic

Optimally Estimating the Sample Standard Deviation from the Five-Number - When reporting the results of clinical studies, some researchers may choose the five-number summary (including the sample median, the first and third quartiles, and the minimum and maximum values) rather than the sample mean and standard deviation (SD), particularly for skewed data. For these studies, when included in a meta-analysis, it is often desired to convert the five-number summary back

Meta-Analysis - an overview | ScienceDirect Topics - Pushpendra K. Gupta, ... Vandana Jaiswal, in Advances in Genetics, 2014. 6.4 Meta-analysis for GWAS. Meta-analysis combines information from multiple GWAS and can increase the chances of finding true positives among the identified associations (Cantor et al., 2010).Hundreds of studies involving GWAS meta-analysis have been published for humans (Evangelou & Ioannidis, 2013), but there seems to

PDF Optimally estimating the sample standard deviation from the five-number - the five-number summary (including the sample median, the first and third quartiles, and the minimum and maximum values) rather than the sample mean and standard deviation (SD), particularly for skewed data. For these studies, when included in a meta-analysis, it is often desired to convert the five-number summary back to the sample mean and SD

5 Tips for Understanding Data in Meta-Analyses - Meta-analysis is a group of statistical techniques that enable data from more than one study to be combined and analyzed as a new dataset. Meta-analysis didn't start to spread until the 1970s. Now there are dozens of publications with meta-analyses every day and it takes less than 5 years for the number published in a year to double

Part E: Finding the Five-Number Summary Numerically (30 minutes - Min, Max and the Five-Number Summary Part E: Finding the Five-Number Summary Numerically (30 minutes) In Part D, we used noodles to help us visualize the concept of quartiles. In practice, however, the task of determining quartiles is treated strictly as a numerical problem. It is based on an ordered list of numerical measurements and the

Statistics lesson 2: How to find the 5 number summary - In this video you learn how to find the 5 number summary from a set of data (highest number, upper quartile, median, lower quartile, lowest number)

PDF PART 5 - Meta-analysis - At this point we can proceed to the meta-analysis using these five (synthetic) scores. To compute a summary effect and other statistics using the fixed-effect model, we apply the formulas starting with (11.3). Using values from the line labeled Sum in Table 23.4, M5 76:667 413:333 50:1855 with variance V M 5 1 413:333 50:0024

Five-number summary and mean - Cross Validated - 5. The five-number summary was, I believe, introduced by John W. Tukey about 1970. The point was that once you have ordered the data ( using a stem-and-leaf plot), then those summaries could be produced by at most counting and averaging pairs of values. The context was pencil and paper methods for tens or (say) a few hundred values

PDF Statistics and Its Interface Volume 13 (2020) 519-531 - number summary, which consists of the minimum value a, ∗Correspondingauthor. theﬁrstquartileq 1, the median m, the third quartile q 3, and the maximum value b. For convenience, we deﬁne the threecommonscenariosasfollows: S 1 =a,m,b;n, S 2 =q 1,m,q 3;n, S 3 =a,q 1,m,q 3,b;n, wherenisthesamplesizeofthedata. To our knowledge, most

Meta-Analysis Methods & Examples | What is Meta-Analysis? - Video - The procedure for performing a meta-analysis can be divided into 5 basic steps. 1. Develop the Research Question: The first step in meta-analysis involves carefully thinking about the topic in

Development of the summary of findings table for network meta-analysis - Objectives: The aim of the study was to develop a Grading of Recommendations, Assessment, Development and Evaluation (GRADE) summary of findings (SoF) table format that displays the critical information from a network meta-analysis (NMA). Study design and setting: We applied a user experience model for data analysis based on four rounds of semistructured interviews

Ten simple rules for carrying out and writing meta-analyses - Meta-analysis is a powerful tool to cumulate and summarize the knowledge in ... Higgins JP (2008) Recent developments in meta-analysis. Stat Med 27: 625-650. pmid:17590884 . View Article ... Torri V, Stewart L (1998) Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med 17: 2815

How to estimate the sample mean and standard deviation from the five - In this paper, we propose an optimal estimator of the standard deviation from the five number summary. Together with the optimal mean estimator in Luo et al. (Stat Methods Med Res, in press, 2017), our new methods have improved the existing literature and will make a solid contribution to meta-analysis and evidence-based medicine

Meta-analysis - Wikipedia - in which is the treatment mean, is the control mean, the pooled variance.; Selection of a meta-analysis model, fixed effect or random effects meta-analysis. Examine sources of between-study heterogeneity, using subgroup analysis or meta-regression.; Formal guidance for the conduct and reporting of meta-analyses is provided by the Cochrane Handbook

Summarizing a Data Set with a Five-Number Summary - Summarize this data set with the five-number summary. Step 1: Order the values from least to greatest. Our list of values from least to greatest is: 25, 28, 29, 34, 35, 37, 39, 43, 45, 48, 52, 54

5 Number Summary: Definition, Finding & Using - Statistics By Jim - The Interquartile Range (IQR) is the distance between the third and first quartile and it is an integral part of the 5 number summary. This range indicates where the middle 50% of the data fall. Conversely, you also know that 50% falls outside this range, 25% above and 25% below the IQR. Like the range, the IQR is also a measure of variability

Optimally estimating the sample standard deviation from the five‐number - Together with the optimal sample mean estimator in Luo et al., our new methods have dramatically improved the existing methods for data transformation, and they are capable to serve as "rules of thumb" in meta-analysis for studies reported with the five-number summary

Five Number Summary | How To Calculate 5 Number Summary - Analyti… - What is five number summary?

Chapter 10: Analysing data and undertaking meta-analyses - Meta-analysis is the statistical combination of results from two or more separate studies. Potential advantages of meta-analyses include an improvement in precision, the ability to answer questions not posed by individual studies, and the opportunity to settle controversies arising from conflicting claims

Detecting the skewness of data from the sample size and the - the ﬁve-number summary back to the sample mean and SD, and then include them in the subsequent meta-analysis. It is noteworthy that these transformation methods have been attracting more attention and been increasingly applied in meta-analysis and evidence-based practice. For example, the sample SD estimation in Wan et al. (2014) and the

5 Number Summary: Definition, Finding & Using - Statistics By Jim - The 5 number summary is an exploratory data analysis tool that provides insight into the distribution of values for one variable. Collectively, this set of statistics describes where data values occur, their central tendency, variability, and the general shape of their distribution

Optimally estimating the sample standard deviation from the - When reporting the results of clinical studies, some researchers may choose the five-number summary (including the sample median, the first and third quartiles, and the minimum and maximum values) rather than the sample mean and standard deviation (SD), particularly for skewed data

New Developments in Meta-analysis with Five-number Summary - New Developments in Meta-analysis with Five-number Summary Jiandong SHI Department of Mathematics Student thesis: Doctoral Thesis User-Defined Keywords Five-number summary Log-normal distribution Mean difference Meta-analysis Normality test Paradox Skewness test Standardized mean difference Cite this Standard

Optimally estimating the sample standard deviation from the - ﬁve-number summary (including the sample median, the ﬁrst and third quartiles, and the minimum and maximum values) rather than the sample mean and stan-dard deviation, particularly for skewed data. For these studies, when included in a meta-analysis, it is often desired to convert the ﬁve-number summary back to