Description: In many studies across different disciplines, detailed measures of the variables of interest are available. If assumptions can be made regarding the direction of effects between the assessed variables, this has to be considered in the analysis. The functions in this package implement the novel approach CIEE (causal inference using estimating equations; Konigorski et al., 2018, <DOI:10.1002/gepi.22107>) for estimating and testing the direct effect of an exposure variable on a primary outcome, while adjusting for indirect effects of the exposure on the primary outcome through a secondary intermediate outcome and potential factors influencing the secondary outcome. The underlying directed acyclic graph (DAG) of this considered model is described in the vignette. CIEE can be applied to studies in many different fields, and it is implemented here for the analysis of a continuous primary outcome and a time-to-event primary outcome subject to censoring. CIEE uses estimating equations to obtain estimates of the direct effect and robust sandwich standard error estimates. Then, a large-sample Wald-type test statistic is computed for testing the absence of the direct effect. Additionally, standard multiple regression, regression of residuals, and the structural equation modeling approach are implemented for comparison.

Title: Weighted summary of cumulative incidence functions
Description: Estimate of cumulative incidence function in two samples. Provide weighted summary statistics based on various methods and weights.

Title: Compositional Impact of Migration
person("Francisco", "Rowe", email = "fcorowe@liverpool.ac.uk", role = ("aut")),
person("Nikos", "Patias", email = "n.patias@liverpool.ac.uk", role = c("aut","cre")),
person("Jorge", "Rodríguez-Vignoli", email = "Jorge.RODRIGUEZ@cepal.org", role = ("aut"))
Description: Produces statistical indicators of the impact of migration on the socio-demographic
composition of an area. Three measures can be used: ratios, percentages and the Duncan index
of dissimilarity. The input data files are assumed to be in an  origin-destination matrix format,
with each cell representing a flow count between an origin and a destination area. Columns are expected
to represent origins, and rows are expected to represent destinations. The first row and column are
assumed to contain labels for each area. See Rodriguez-Vignoli and Rowe (2018)