2.4. Meta-Analysis: Method of analysis using diverse datasets
Meta-analysis is a potential statistical approach to analyze the reaction of managements (BL/CL/GL/HL/PL) to control treatment (FL) from differentdistinct studies evolving a universal trend. This study has attracted researchers from all over the world for better understanding of all the variables.
Two stage-based Meta-analyses (MetaWin 2.1) were used to analyse the database and understand the comparative changes (Chakraborty et al ., 2017; Rosenberg et al ., 2000). Under this the effect size (ES) was calculated for individual parameter using the equation as proposed by Hedges et al. (1999):
\begin{equation} ES\ =\ lnR=\ln\left[\frac{X_{T}}{X_{C}}\right]\nonumber \\ \end{equation}
Where,
XT-Average of response variables (SOC, SCS, yield and other parameters) of the treatments (LU),
XC-Average of these variables in FL with control
Since, all studies were from variable conditions was the basis of multiple replications, the standard deviation calculated were based on the number of observations with simple statistically procedure.
ES from individual studies were then combined using a mixed-effect model to calculate the cumulative effect size and the 95% confidence intervals (CIs) through bootstrapping with 4999 iterations (Adamset al ., 1997). The mixed-effect model is a random-effect Meta-analytic model for categorical data (Rosenberg et al ., 2000), assuming random variation among studies within a group and fixed variation between groups. The cumulative effect was considered significant if the CIs did not pass over zero.
Interpretation of results : Results were back-transformed and presented as change in percent caused by treatments in relation to control. Significant differences were considered only p value is less than 0.05. The Meta-analysed value has been presented in graph to clearly show the significant effect of LUC and INM over the inorganic fertilizer alone.