find_b.Rd
Estimate regression coefficients
find_B(model_input, R)
model_input | Model input as a character string. Multiple models need to be on their own line. Model syntax uses lavann like syntax, see details for more details about this syntax. |
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R | A correlation matrix, most likely this will be the average correlation matrix outputted from the metafor package. |
A list of parameter estimates
Detailed examples of lavaan like syntax can be found: http://lavaan.ugent.be/tutorial/syntax1.html.
The output will be the same length as the number of regression equations specified in the model_input argument.
Br <- matrix(c(1.00000000, -0.09773331, -0.1755029, 0.3186775, -0.09773331, 1.00000000, 0.5271873, -0.4175596, -0.17550292, 0.5271872, 1.0000000, -0.4006848, 0.31867753, -0.41755963, -0.4006848, 1.0000000), nrow = 4, byrow = TRUE) colnames(Br) <- c("Performance", "Self_confidence", "Cognitive", "Somatic" ) rownames(Br) <- colnames(Br) ## Proposed path model model <- "## Regression paths Performance ~ Self_confidence + Cognitive + Somatic Self_confidence ~ Cognitive + Somatic " find_B(model, Br)#> [[1]] #> Self_confidence -> Performance Cognitive -> Performance #> 0.08316153 -0.09261001 #> Somatic -> Performance #> 0.31629500 #> #> [[2]] #> Cognitive -> Self_confidence Somatic -> Self_confidence #> 0.4287053 -0.2457839 #>