In johninpdx/JMLUtils: Wrappers for R administration, general statistics, data management

load("V:Research/Papers/SOR.NSUTx/SUTx.w123456.RData")

save.image("V:Research/Papers/SOR.NSUTx/SUTx.w123456.RData")

packages <- c("data.table", "keyring", "blastula",
              "tidyverse", "dtplyr", "naniar",
              "network", "sna", "RHNetTools", "Matrix", "RSiena", 
              "JMLUtils", "haven", "glue")
if(length(setdiff(packages, rownames(installed.packages))) > 0) {
  lapply(packages, library, character.only = TRUE)
}
# If necessary (RSienaTest is not on Cran):
#install.packages("RSienaTest", repos="http://R-Forge.R-project.org")
workingDir <- here::here()

Mod48<- readRDS("V:/Research/Papers/SOR.NSUTx/Mod48.RDS")

Mod 48 (test model)

print(Mod48)
tM <- Mod48

RFEgo (12) is g1 (primary) RFAlt (11) is moderator (g2) RFEgo x RFAlt (13) is interac term

NOTE: when you specify the covariance between g1 and g3, be sure it's above the diagonal so, the row should always be LESS THAN the column!!)

Ego (12) is primary, alt(11) is mod

mod <- tM
g1 <- mod$theta[12] #Beta: primary (ego)
g2 <- mod$theta[11] #Beta: moderator (alt)
g3 <- mod$theta[13] #Beta: interaction
g1Var <- mod$covtheta[12,12] #Var primary
g2Var <- mod$covtheta[11,11] #Var moderator
g3Var <- mod$covtheta[13,13] #Var (prim x mod)
g1g3Cov <-mod$covtheta[12,13] #Cov(prim, int)
tSq <- 1.96*1.96 #squared critical value (for .05 2-tailed)

Calculate quadratic coefficients ac, bc, cc

ax <- (tSq*g3Var) - g3^2
bx <- 2*((tSq*g1g3Cov) - (g1*g3))
cx <- (tSq*g1Var) - g1^2
# Will the equation have real roots?
isThisPos<-(bx^2)-(4*ax*cx) #If it isn't, the equation has no real roots.
ax
bx 
cx

Quadratic formula

rootPos.ep <- (-bx + sqrt((bx^2)-(4*ax*cx)))/(2*ax)
rootNeg.ep <- (-bx - sqrt((bx^2)-(4*ax*cx)))/(2*ax)

rootPos.ep = -3.615 rootNeg.ep = 0.850

Check ep eq roots.

The equation is: $$f(e)= -0.03068e^2 - 0.08484e + 0.09425 = 0$$ This calculation should be 0 for either rootPos or rootNeg. Both are.

ax*(rootNeg.ep^2) + (bx*rootNeg.ep) + cx
ax*(rootPos.ep^2) + (bx*rootPos.ep) + cx

JNSiena on same model

JNSiena(siena07out = tM,
        theta1=12, #ego is primary in 1st dataframe
        theta2=11, #alt is moderator in 1st dataframe
        thetaInt = 13,
        theta1vals = c(-3.7, 0.5, 0.6, 0.7, 0.8, 0.9,  1),
        theta2vals = c(-3.7, 0.5, 0.6, 0.7, 0.8, 0.9,  1),
        sigRegion = TRUE,
        alpha=0.05
        )

Alt (11) is primary, ego (12) is mod

RFAlt (11) is g1 (primary) RFEgo (12) is moderator (g2) RFEgo x RFAlt (13) is interac term

mod <- tM
g1 <- mod$theta[11] #Beta: primary (alt)
g2 <- mod$theta[12] #Beta: moderator (ego)
g3 <- mod$theta[13] #Beta: interaction
g1Var <- mod$covtheta[11,11] #Var primary
g2Var <- mod$covtheta[12,12] #Var moderator
g3Var <- mod$covtheta[13,13] #Var (prim x mod)
g1g3Cov <-mod$covtheta[11,13] #Cov(prim, int)
tSq <- 1.96*1.96 #squared critical value (for .05 2-tailed)

Calculate quadratic coefficients ax, bx, cx

ax <- (tSq*g3Var) - g3^2
bx <- 2*((tSq*g1g3Cov) - (g1*g3))
cx <- (tSq*g1Var) - g1^2
# Will the equation have real roots?
isThisPos<-(bx^2)-(4*ax*cx) #If it isn't, the equation has no real roots.
ax
bx 
cx

Quadratic formula

rootPos.ap <- (-bx + sqrt((bx^2)-(4*ax*cx)))/(2*ax)
rootNeg.ap <- (-bx - sqrt((bx^2)-(4*ax*cx)))/(2*ax)

rootPos.ap = -4.88 rootNeg.ap = 0.604

johninpdx/JMLUtils documentation built on Dec. 29, 2024, 1:27 p.m.