Nursing Practice Today Volume 7, No 1, January 2020, pp. 5-11 Tehran University of Medical Sciences Editorial Practical calculation of mean, pooled variance, variance, and standard deviation, in meta- analysis studies Mahdieh Arian1, Mohsen Soleimani2* 1 Student Research Committee, Faculty of Nursing and Midwifery, Semnan University of Medical Sciences, Semnan, Iran 2 Nursing Care Research Center, Nursing and Midwifery Faculty, Semnan University of Medical Sciences, Semnan, Iran 1Meta-analysis is known as a statistical between variables or researchers’ desired analysis that combines the results of multiple effects. Moreover, these tests can merely scientific studies. Meta-analysis can be indicate that the relationships observed in performed when there are multiple scientific the findings do not arise out of chance. studies addressing the same question, with Although statistical significance testing each individual study reporting makes researchers not to interpret the measurements that are expected to have substantial differences between small some degree of error (1). The aim then is to statistical populations as significant, these use approaches from statistics to derive a tests cannot prevent the consideration of pooled estimate closest to the unknown significance associated with very small common truth based on how this error is differences in large populations (4). As perceived (1, 2). Following the selection of a stated by Kirk (1996), “small differences in research topic, researchers need to identify large populations can be statistically the related literature on the specified subject significant”(5). Critics also believe that from all data sources and subsequently significance levels and effect size indices extract any evidence from available should be taken into account in the analysis scientific documents called Systematic of findings (6). Therefore, it is of utmost Review (SR). The data included can be importance to employ such integration associated with levels of measurement for methods endowed with effect sizes. variables, dominant theoretical model or Means using a dispersion index such as approach, significance level, effect size, standard deviation or pooled variance are effect or direction of a relationship, and types of effect sizes and in the meta-analysis sample size (2). studies, the effect size of the primary studies Afterward, researchers make use of the should be correctly recorded or estimated. existing statistical methods such as It should be noted that effect size is a logarithmic integration, T-score, probability quantitative measure by which statistical integration, Z-score, P-test, counting results can be combined, summarized, and method, and blocking to combine the results homogenized. Effect size has recognized as of studies. Regarding the advantages and a critical element in the meta-analysis; in limitations of each method, researchers fact, effect size makes met-analysis possible. select an appropriate one (3). According to Accordingly, the main purpose to employ Carver (1993), these tests can only represent effect sizes is to equalize different statistical a small and concise index or reflection of findings in a numeric scale and common statistical significance associated with the measure in order to provide the possibility of results of a hypothesis and they fail to show comparisons and combinations of statistical the strength or intensity of relationships results of different studies (7). Besides, the effect size can have several categories, but the most common effect size equations are *Corresponding Author: Mohsen Soleimani, Nursing Care Research Center, Faculty of Nursing and Midwifery, Semnan University of extracted based on three data types including Medical Sciences, Semnan, Iran. Email: [email protected] means, binary data, and correlations, which DOI: https://doi.org/10.18502/npt.v7i1.2294 Please cite this article as: Arian M, Soleimani M. Practical calculation of mean, pooled variance, variance and standard deviation, in meta-analysis studies. Nursing Practice Today. 2020; 7(1):5-11 Estimation of parameters in meta-analysis make it possible to complete a meta- range of such equations has been also analysis. The most common effect size proposed by Borenstein et al. (2009) (3). equations are presented in Table 1. A wide Table 1. Roadmap of formulas (3) Effect sizes based on means Raw (unstandardized) mean difference (D) Based on studies with independent groups Based on studies with matched groups or pre-post designs Standardized mean difference (d or g) Based on studies with independent groups Based on studies with matched groups or pre-post designs Response ratios (R) Based on studies with independent groups Effect sizes based on binary data Risk ratio (RR) Based on studies with independent groups Odds ratio (OR) Based on studies with independent groups Risk difference (RD) Based on studies with independent groups Effect sizes based on correlational data Correlation (r) Based on studies with one group As observed in the above classifications, distribution-free. The value of our effect size based on means may be related to approximation(s) is in giving a method for the difference between two means in a raw estimating the mean and the variance exactly form or difference between two means in a when there is no indication of the underlying standard form or even ratio of two means. distribution of the data (8, 9) Sometimes, effect size based on means may Furthermore, an exact method of also be associated with cross-sectional and calculating the variance of a pooled data set is single-group studies in which the means of presented. These estimations are distribution- the same groups will be counted as effect free, i.e., they do not assume the distribution sizes. To perform a meta-analysis on of the underlying data. The advantages of continuous data, there is also a need for effect using the exact pooled variance include that it size based on means using a dispersion index is simple, requires no assumptions, is exact, is such as variance or standard deviation to pool easily understood and remembered, is the data. However, in one possible case, pedagogically helpful, and can yield evidence clinical trials may only report median, range, for possible consistent errors suggesting and sample size. Otherwise, the total mean rejection of the pooling and/or investigation and standard deviation or pooled variance of the measurements. might not be reported (8). For example, in a multi-dimensional questionnaire, researchers may merely compare the means of each 1. Detailed calculation of pooled variance dimension of the questionnaire, and total Pooled Variance is the mean of the mean and standard deviation or total variance may not be reported even with the presence variances plus the variance of the means, of standard deviation for each dimension. The which is a set of combined data. First, the present study was an attempt to estimate calculation method and then the applied mean and standard deviation in such studies example is presented (9). The integrated wherein effect size is not reported or the corresponding author does not respond, based variance will be accurately calculated in eight on elementary and straightforward steps. Suppose you have numeric sets of a inequalities. These estimates will be also variable. These sets include: 6 Nursing Practice Today. 2020;7(1):5-11 M. Arian et al. The mean or average of is . Means , and for , , and , are found similarly. Then the mean of the means. The sum of squares is . Sums , , and are similarly defined for sets , , and . Then Define the variance of data set to be . Expanding the argument easily shows That Similarly, , , and Our goal is to calculate from the means and variances of the constituent sets. From , , and , Or The mean of the variances is From, the variance of the means is Or Pooled variance is combining,, and yields QED So the Pooled Variance is the mean of analysis study is performed on the the variances plus the variance of the means questionnaire (SF-36) related to health- (9). The importance of these calculations is related quality of life. This questionnaire very significant at the time of writing a has two main summaries, each of which is meta-analysis study. Suppose that a meta- obtained from the sum of Nursing Practice Today. 2020;7(1):5-11 7 Estimation of parameters in meta-analysis four dimensions and the total score of this Example: According to the study of La questionnaire is the sum of eight Nasa et al. (2013), the mean and standard dimensions. Now, suppose that in one of deviation of eight dimensions of health- the studies introduced into a meta-analysis, related quality of life have been extracted you have access to the scores of eight from the control group with a sample size dimensions but you do not have two of 124 subjects and listed in Table 2 (10). summary scores and total score. Through Based on the information in the article, the the formulas above, we can calculate the mean and standard deviation of dimensions summary scores and total score. of PCS, MCS, and HRQOL has been calculated below. Table 2. The mean and standard deviation of eight dimensions of health-related quality of life in the control group in the study of La Nasa et al. (2013) (10) PF RP BP GH PCS VT SF RE MH MCS HRQOL Mean 90.42 71.45 63.29 65.24 ? 64.63 83.64 74.37 73.95 ? ? (SD) 12.68 34.5 27.43 22.82 ? 17.95 23.46 36.05 20.31 ? ? Physical Function (PF), Role Physical (RP), Bodily Pain (BP), General Health (GH), Vitality (VT), Social Function (SF), Role Emotional (RE), Mental Health (MH), Mental Component Summary (MCS( , Physical Component Summary )PCS( First, initial mean values should be and the numbers obtained are summed then, multiplied by the sample size, in the present divided by the number obtained from the example, since the mean values are related product of the number of dimensions and the to the dimensions of a tool, therefore, the sample size.