rep_consensus_builder: Reputation Consensus Model Builder

Description Usage Arguments Value Examples

View source: R/reputation_model.R

Description

This takes a vector of P1 and P2 reports and builds a model of lavaan syntax for estimating the possible hearsay reputation parameters. Those parameters are:

hc

hearsay consensus; the correlation between P1(T) & P2(T)

int_p1

Intercept for P1(T)

int_p2

Intercept for P2(T)

v_p1

variance for P1(T)

v_p2

variance for P2(T)

p1_p2_rel_el

P1-P2 Relative Elevation (i.e., Mean P1(T) - Mean P2(T))

If n exchangeable triads > 1:

rec

direct reciprocity; the correlation between opposit P1(T)s (e.g., A(C) <-> C(A))

h

hearsay reciprocity; the correlation between exchangeable P2(T)s (e.g., B(C) <-> D(A))

m

unnamed parameter; The correlation between P2(T) and the opposite P1(T) in a group. (e.g., B(C) <-> C(A))

The function can handle up to n exchangeable triads.

Usage

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rep_consensus_builder(p1_reports, p2_reports,
  n_triads = length(p1_reports), n_p1s_per_p2s = 1,
  n_p2s_per_p1s = 1)

Arguments

p1_reports

Quoted column names that contain P1 reports, or ratings made by the person that knows the target directly. If more than one is supplied, the target-wise order must match the other rating types.

p2_reports

Quoted column names that contain P2 reports, or ratings made by the person that knows the target indirectly through the corresponding P1. If more than one is supplied, the target-wise order must match the other rating types.

n_triads

The number of exchangeable triads in each group. By default, this is determined by counting the number of P1 reports. This parameter rarely needs to be changed.

n_p1s_per_p2s

The number of P1s for every P2. This defaults to 1. Currently, only values of 1 are supported.

n_p2s_per_p1s

The number of P2s for every P1;. This defaults to 1. Currently, only values of 1 are supported.

Value

The function returns a list containing an object of class tbl_df and a string object of the model in lavaan syntax. Model information includes the type of model, the number of exchangeable triads, and the number of p1s per p2s, and the number of p2s per p1s.

Examples

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         # build the model
          agree_consensus_model <- rep_consensus_builder(p1_reports = c("A_C_agreeableness", "C_A_agreeableness"),
          p2_reports = c("B_C_agreeableness", "D_A_agreeableness"))

         # view the model
         agree_consensus_model$model

         # view the model information
         # agree_consensus_model$rep_model_info

Coryc3133/ReputationAnalyses documentation built on July 31, 2019, 8:35 a.m.