srm (version 0.3-6)

srm_arbsrm: Least Squares Estimation of the Social Relations Model (Bond & Malloy, 2018)

Description

Provides least squares estimation of the bivariate social relations model with missing completely at random data (Bond & Malloy, 2018a). The code is basically taken from Bond and Malloy (2018b) and rewritten for reasons of computation time reduction.

Usage

srm_arbsrm(data, serror = TRUE, use_srm = TRUE)
# S3 method for srm_arbsrm
coef(object, ...)
# S3 method for srm_arbsrm
summary(object, digits=3, file=NULL, ...)

Value

List containing entries

par_summary

Parameter summary table

est

Estimated parameters (as in Bond & Malloy, 2018b)

se

Estimated standard errors (as in Bond & Malloy, 2018b)

Arguments

data

Rectangular dataset currently containing only one round robin group. Bivariate observations are stacked one below the other (see example dataset data.bm1).

serror

Logical indicating whether standard errors should be calculated.

use_srm

Logical indicating whether the rewritten code (TRUE) or the original code of Bond and Malloy (2018b) should be used.

object

Object of class srm_arbsrm

file

Optional file name for summary output

digits

Number of digits after decimal in summary output

...

Further arguments to be passed

Author

Rewritten code of Bond and Malloy (2018b). See http://thomasemalloy.org/arbsrm-the-general-social-relations-model/ and http://thomasemalloy.org/wp-content/uploads/2017/09/arbcodeR.pdf.

References

Bond, C. F., & Malloy, T. E. (2018a). Social relations analysis of dyadic data structure: The general case. In T. E. Malloy. Social relations modeling of behavior in dyads and groups (Ch. 14). Academic Press. tools:::Rd_expr_doi("10.1016/B978-0-12-811967-9.00014-X")

Bond, C. F., & Malloy, T. E. (2018b). ARBSRM - The general social relations model. http://thomasemalloy.org/arbsrm-the-general-social-relations-model/.

See Also

Without missing data, ANOVA estimation can be conducted with the TripleR package.

Examples

#############################################################################
# EXAMPLE 1: Bond and Malloy (2018) illustration dataset
#############################################################################

data(data.bm2, package="srm")
dat <- data.bm2

#- estimation
mod1 <- srm::srm_arbsrm(dat)
mod1$par_summary
coef(mod1)
summary(mod1)

# \donttest{
#-- estimation with original Bond and Malloy code
mod1a <- srm::srm_arbsrm(dat, use_srm=FALSE)
summary(mod1a)
# }