Ten circumstances and solutions for finding the sample mean and standard deviation for meta-analysis

Abstract

A common problem in meta-analyses is the unavailability of mean and standard deviation (SD). Unfortunately, only having values of the median, interquartile range (IQR), or range cannot be directly utilized for meta-analysis. Although some estimation and conversion methods have been proposed in the past two decades, there were no published and user-friendly tools developed based on multiple scenarios of missing SD. Therefore, this study aimed to provide a collection of possible circumstances of missing sample means or SD with solutions for teaching and research. A total of 10 common circumstances of missing SD or mean could have available statistics of p value, t value, z score, confidence interval, standard error, median, IQR, and range. Teachers and investigators can use relevant formulas for finding the sample mean and SD according to the available circumstance. Due to the complicated computations, our team provides a free available spreadsheet. With ever-evolving statistical methods, some formulas may be further improved in the future; therefore, it is recommended to involve statisticians in evidence-based practice or systematic reviews.

Securing cloud data using secret key 4 optimization algorithm (SK4OA) with a non-linearity run time trend

“…Also, with a σ encryption and decryption memory of ±0.111, ±0.122, ±0.168, ±0.146, ±0.201, ±0.111, ±0.122, ±0.146, ±0.168 and ±0.201 respectively for data size of 3KB, 5KB, 8KB, 12KB and 16KB, the memory sizes are clustered around the mean [ 43 ]. This implies that, the size of the memory consumed is close to the mean and the difference of utilized memory is not very significant [ 44 ].…”

Effectiveness of Air Filters in Allergic Rhinitis: A Systematic Review and Meta-Analysis

“…Some methods require expertise and are currently unavailable in standard meta-analysis software, limiting accessibility for the majority of systematic reviewers. Therefore, experts consistently improve the missing data conversion process [81], allowing systematic reviewers to obtain the maximum information from included studies when original data is inaccessible.…”

Treatment Response With Potassium-competitive Acid Blockers Based on Clinical Phenotypes of Gastroesophageal Reflux Disease: A Systematic Literature Review and Meta-analysis

“…Appropriate conversion or estimation can increase accuracy and reduce the risk of bias from incomplete reporting. 35 Conversely, skewed results may bias estimates, and observed differences may be further influenced by expansion of the size of the intervention group and when standard deviation is underestimated during conversion, potentially affecting the outcomes. To overcome this, sensitivity analysis was conducted with combinations of drug types and all doses, and the same results were obtained, with a heterogeneity of 0%, indicating low inter-study variability.…”

“…For the meta-analysis of NERD, we converted values presented as median ± quartile into mean ± standard deviation in 2 vonoprazan studies according to formulas in the Cochrane Handbook. 22 , 23 , 35 In PPI-resistant GERD, pooled prevalence rates were analyzed only for studies with consistent outcomes. In the analysis of TEAEs, serum gastrin levels were presented graphically on a continuous scale.…”