R/rpathways.R

In validmeasures/rpathways: An Implementation of the Results Pathways Monitoring in R

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#
#' rpathways
#'
#' An Implementation of the Results Pathways Monitoring in R
#'
#' Results pathways are usually based on a theory of change describing
#' how change is assumed to come about through intervention/s in a prevailing
#' situation. The theory is laid out in a diagram showing the connections
#' between interventions and outcomes - the results pathways. From an
#' epidemiological perspective, these results pathways can be conceived as
#' directed acyclic graphs (DAG) more specifically those concerned with
#' structural causal models that portray causal assumptions about a set of
#' variables. Causal DAGs are consistent and easy to understand. Thus, when
#' assessing the causal effect between an intervention and an outcome, drawing
#' assumptions in the form of a DAG can help in picking the right model without
#' necessarily having the mathematical basis behind it. Another way to think
#' about DAGs is as non-parametric structural equation models (SEM) which
#' explicitly lays out paths between variables. In the case of a DAG, the
#' exact relationship between the two variables is not as important, only its
#' direction. The rules underpinning DAGs are consistent whether the
#' relationship is da simple, linear one, or a more complicated function.
#'
#' @docType package
#' @name rpathways
#'
#
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