Performs causal mediation analysis for count and zero-inflated
    count data without or with a post-treatment confounder; calculates power
    to detect prespecified causal mediation effects, direct effects, and 
    total effects; performs sensitivity analysis when there is a treatment-
    induced mediator-outcome confounder as described by Cheng, J., Cheng, N.F., 
    Guo, Z., Gregorich, S., Ismail, A.I., Gansky, S.A. (2018) 
    <doi:10.1177/0962280216686131>. Implements Instrumental Variable (IV) 
    method to estimate the controlled (natural) direct and mediation effects, 
    and compute the bootstrap Confidence Intervals as described by Guo, Z., 
    Small, D.S., Gansky, S.A., Cheng, J. (2018) <doi:10.1111/rssc.12233>. This 
    software was made possible by Grant R03DE028410 from the National 
    Institute of Dental and Craniofacial Research, a component of the National 
    Institutes of Health.

A collection of functions for conducting a meta-analysis with mean differences data.  It uses recommended procedures as	described in The 	Handbook of Research Synthesis and Meta-Analysis	(Cooper, Hedges, & Valentine, 2009).

Provides functions for diagnostic meta-analysis. Next to basic analysis and visualization the bivariate Model of Reitsma et al. (2005) that is equivalent to the HSROC of Rutter & Gatsonis (2001) can be fitted. A new approach based to diagnostic meta-analysis of Holling et al. (2012) is also available. Standard methods like summary, plot and so on are provided.

This is an open-source software designed specifically for text mining in the Persian language. It allows users to examine word frequencies, download data for analysis, and generate word clouds. This tool is particularly useful for researchers and analysts working with Persian language data.
    This package mainly makes use of the 'PersianStemmer' (Safshekan, R., et al. (2019). <https://CRAN.R-project.org/package=PersianStemmer>),
    'udpipe' (Wijffels, J., et al. (2023). <https://CRAN.R-project.org/package=udpipe>),
    and 'shiny' (Chang, W., et al. (2023). <https://CRAN.R-project.org/package=shiny>) packages.