rep_full_3pmeta_group_mod_builder: Reputation Consensus, Accuracy, and 3rd-Person...

In Coryc3133/ReputationAnalyses: Functions to model and analyze triadic (T-P1-P2) reputational data

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))

tru_sim

True Similarity; the correlation between targets' self-reports. (e.g., A(A) <-> C(C))

as_sim_3p

Third-person assumed similarity; correlation between P2(T) and P1's self-report (e.g., B(C) <- A(A))

as_sim_1p

First-person assumed similarity (i.e., interpersonal assumed similarity); correlation between P1(T) and P1's self-report (e.g., A(C) <-> A(A))

as_sim_p1m

P1 Meta-assumed similarity (e.g., A(B(C)) <-> A(A))

ukp1m1

unknown p1-meta 1

P1 meta-perception with opposite P1-report (e.g., A(B(C)) <-> C(A))).

p1meta_sim

P1 Meta-Similarity

correlation between exchangeable P1 meta-perceptions (e.g., A(B(C)) <-> C(D(A))).

ukp2m1

unknown P2-meta 1

P2 Meta-perception with exchangeable P2-reports (e.g., B(A(C)) <-> D(A))

ukp2m2

unknown P2-meta 2

P2 Meta-perception with exchangeable target self-report (e.g., B(A(C) <-> A(A)))

ukp2m3

unknown P2-meta 3

P2 Meta-perception with exchangeable P1-reports (e.g., B(A(C)) <-> C(A))

p2meta_sim

P2 Meta-Similarity

correlation between exchangeable P2 meta-perceptions (e.g., B(A(C)) <-> D(C(A))).

ukm1

unknown Meta-perception

P1 Meta-perception with exchangeable P2 Meta-Perception (e.g., A(B(C)) <-> D(C(A)))

Description

The function can handle up to n exchangeable triads.

Usage

rep_full_3pmeta_group_mod_builder(p1_reports, p2_reports, target_self,
  p1_meta, p2_meta, groups = NULL, use_labs = TRUE,
  n_triads = length(p1_reports), n_p1s_per_p2s = 1,
  n_p2s_per_p1s = 1, n_p1s_per_ts = 1, n_p2s_per_ts = 1,
  n_ts_per_p1s = 1, n_ts_per_p2s = 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.
target_self	Quoted column names that contain target self-reports. If more than one is supplied, the target-wise order must match the other rating types.
p1_meta	Quoted column names that contain P1 3rd person Meta-perceptions, or P1's ratings of how they think P2 sees the target. If more than one is supplied, the target-wise order must match the other rating types.
p2_meta	Quoted column names that contain P2 3rd person Meta-perceptions, or P2's ratings of how they think P1 sees the target. If more than one is supplied, the target-wise order must match the other rating types.
groups	Vector of quoted group labels (from group-level categorical moderator).
use_labs	Logical indicating whether or not to use the group labels to create the parameter labels. If FALSE, generic labels (grp1 to grpk, where k is the number of groups) are used.
n_triads	The number of exchangeable triads in each group. By default, this is determined by counting the number of P1 reports. It is rare that this parameter would need 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.
n_p1s_per_ts	The number of P1s for every target;. This defaults to 1. Currently, only values of 1 are supported.
n_p2s_per_ts	The number of P2s for every target;. This defaults to 1. Currently, only values of 1 are supported.
n_ts_per_p1s	The number of targets for every P1;. This defaults to 1. Currently, only values of 1 are supported.
n_ts_per_p2s	The number of targets for every P2;. 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, the number of p2s per target, and the number of targets per p2s, the number of targets per p1s, and the number of p1s per target.

Examples

data("rep_sim_data")
          rep_full_3pmeta_model <- rep_full_3pmeta_group_mod_builder(p1_reports = c("A_C_agreeableness", "C_A_agreeableness"),
                                                             p2_reports = c("B_C_agreeableness", "D_A_agreeableness"),
                                                             target_self = c("C_C_agreeableness", "A_A_agreeableness"),
                                                             p1_meta = c("A_B_C_agree_meta", "C_D_A_agree_meta"),
                                                             p2_meta = c("B_A_C_agree_meta", "D_C_A_agree_meta"),
                                                             groups = c("Study_1", "Study_2"))

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