Description: It is a computer tool to conduct mediation analysis for complex surveys using multi-stage sampling. Specifically, the mediation analysis method using balanced repeated replication was proposed by Mai, Ha, and Soulakova (2019) <DOI:10.1080/10705511.2018.1559065>. The development of 'MedSurvey' was sponsored by American Lebanese Syrian Associated Charities (ALSAC). However, the contents of MedSurvey do not necessarily represent the policy of the ALSAC.

Title: Linear Mediation Analysis for Complex Surveys Using Balanced
Description: It is a computer tool to conduct linear mediation analysis for complex surveys using multi-stage sampling and Balanced Repeated Replication (BRR). Specifically, the mediation analysis method using balanced repeated replications was proposed by Mai, Ha, and Soulakova (2019) <DOI:10.1080/10705511.2018.1559065>. The current version can only handle continuous mediators and outcomes. The development of 'MedSurvey' was sponsored by American Lebanese Syrian Associated Charities (ALSAC). However, the contents of MedSurvey do not necessarily represent the policy of the ALSAC.

Author: Zizhuo Ren, Hesen Peng, Tianwei Yu
Description: Calculates MeDiA_K (means Mean Distance Association by K-nearest neighbor) in order to detect nonlinear associations.
Packaged: 2015-12-24 09:33:04 UTC; renzizhuo

Title: Media News Extraction for Text Analysis
Description: Extract textual data from different media channels
through its source, based on users choice of keywords.
These data can be used to perform text analysis to
identify patterns in respective media reporting.
The media channels used in this package are print media
from India. The data (or news) used are publicly

through its source based on users choice of keywords.
The media channels used in this package are print media.
The data (or news) used are publicly available to consumers.

Description: Provides a general framework for clinical trial simulations based on the Clinical Scenario Evaluation (CSE) approach. The package supports a broad class of data models (including clinical trials with continuous, binary, survival-type and count-type endpoints as well as multivariate outcomes that are based on combinations of different endpoints), analysis strategies and commonly used evaluation criteria.
Imports: doParallel, doRNG, foreach, MASS, mvtnorm, ReporteRs, stats,