tests/testthat/test-PartInv_multi.R
In claycantrell/PartInvShinyUI: Multidimensional Classification Accuracy Analysis Framework
result <- structure(
list(`1` = list(
lambda = structure(
c(0.321851420828946,
0.65505328221763, 0.644928823284184, 0.745498551641102, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.569789973707324,
0.341398323887283, 0.397589912762831, 0.745400693889335, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.6572331474069,
0.803018980949713, 0.798604339572203, 0.685778873051152, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.50691173408154,
0.824339800976872, 0.599603442972015, 0.825307748488813, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.511822774613899,
0.425281197599131, 0.484803397473042, 0.569706848613303),
.Dim = c(20L, 5L),
.Dimnames = list(c("a2", "a5", "a7", "a9", "c3", "c4", "c8",
"c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6", "n8", "i2", "i8",
"i9", "i10"),
c("A", "C", "E", "N", "O")),
class = c("lavaan.matrix", "matrix")),
theta = structure(
c(0.543886582321731, 0.172041746020309,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0120358623284618, 0, 0, 0, 0, 0,
0, 0, 0, 0.172041746020309, 0.536443955046005, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.410358018613791,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.356096075938922,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.148959243230043,
0, 0, 0, 0, 0, 0.934929805416671, 0, 0, 0, 0, 0, -0.232254971317054,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.409621144057789,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.495104906416798,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.924828156814879,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.78444201074091,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.991446629333851,
0, -0.1069952336659, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.232254971317054,
0, 0, 0, 0, 0, 0.880871827235737, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.0120358623284618, 0, 0, 0, 0, 0, 0, 0, 0, -0.1069952336659,
0, 0.611527086912206, 0, -0.0226876197802865, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.66269941620454, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.0226876197802865,
0, 0.569648257556627, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.747797205162342, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.651913135519311, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.73485217216192,
0, 0, 0.312250352868153, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1.18247806913975, 0.457286841547525, 0, 0, 0,
0, 0.148959243230043, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.457286841547525, 1.01537514466963, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.312250352868153, 0, 0, 0.785695412105443
),
.Dim = c(20L, 20L),
.Dimnames = list(c("a2", "a5", "a7", "a9",
"c3", "c4", "c8", "c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6",
"n8", "i2", "i8", "i9", "i10"),
c("a2", "a5", "a7", "a9", "c3",
"c4", "c8", "c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6", "n8",
"i2", "i8", "i9", "i10")),
class = c("lavaan.matrix.symmetric", "matrix")),
psi = structure(
c(1, 0.0307300527642325, 0.397826036072362,
-0.190732145703416, 0.416212032411235, 0.0307300527642325, 1,
0.0516464797818452, -0.1590078212592, -0.00935598159738081, 0.397826036072362,
0.0516464797818452, 1, -0.0409034475100417, 0.672259531068557,
-0.190732145703416, -0.1590078212592, -0.0409034475100417, 1,
-0.0589307820291875, 0.416212032411235, -0.00935598159738081,
0.672259531068557, -0.0589307820291875, 1),
.Dim = c(5L, 5L),
.Dimnames = list(c("A", "C", "E", "N", "O"), c("A", "C", "E", "N", "O")),
class = c("lavaan.matrix.symmetric","matrix")),
nu = structure(
c(3.94424798096106, 3.56191664603162,
3.99887279416986, 3.61846568375092, 3.28727563899424, 4.26318382086251,
4.18115621522395, 3.59932137934746, 2.26973604341351, 2.92379355460568,
3.01186745338878, 3.09054924993737, 2.25941455787935, 2.46014063678953,
2.32370361993874, 2.27867084045946, 3.97168549581889, 3.59000455755382,
3.61505997818372, 4.07151827816703),
.Dim = c(20L, 1L),
.Dimnames = list(
c("a2", "a5", "a7", "a9", "c3", "c4", "c8", "c9", "e1", "e4",
"e6", "e7", "n1", "n2", "n6", "n8", "i2", "i8", "i9", "i10"
), "intercept"), class = c("lavaan.matrix", "matrix")),
alpha = structure(c(0, 0, 0, 0, 0),
.Dim = c(5L, 1L),
.Dimnames = list(c("A", "C", "E", "N", "O"), "intercept"),
class = c("lavaan.matrix", "matrix"))),
`2` = list(
lambda = structure(
c(0.321851420828946, 0.65505328221763,
0.644928823284185, 0.745498551641103, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.569789973707324,
0.341398323887284, 0.397589912762831, 0.745400693889336,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.6572331474069, 0.803018980949713, 0.798604339572203,
0.685778873051152, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.50691173408154, 0.824339800976872,
0.599603442972015, 0.825307748488813, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.511822774613899,
0.425281197599131, 0.484803397473042, 0.569706848613303),
.Dim = c(20L, 5L),
.Dimnames = list(c("a2", "a5", "a7", "a9", "c3", "c4",
"c8", "c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6", "n8",
"i2", "i8", "i9", "i10"),
c("A", "C", "E", "N", "O")),
class = c("lavaan.matrix", "matrix")),
theta = structure(
c(0.543886582321732, 0.0991628559089238,
0, 0, 0, 0, 0, 0, 0, 0, 0, -0.115517592631624, 0, 0, 0, 0,
0, 0, 0, 0, 0.0991628559089238, 0.536443955046005, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.410358018613791,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.356096075938922, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, -0.00550535625446915, 0, 0, 0, 0, 0, 0.934929805416671,
0, 0, 0, 0, 0, -0.0296478578193999, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.409621144057789, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.70483713633214,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.924828156814879, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0.78444201074091, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.991446629333851,
0, -0.082909427455581, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-0.0296478578193999, 0, 0, 0, 0, 0, 0.880871827235738, 0,
0, 0, 0, 0, 0, 0, 0, 0, -0.115517592631624, 0, 0, 0, 0, 0,
0, 0, 0, -0.082909427455581, 0, 0.611527086912206, 0, -0.146167079574639,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.943687415419278,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.146167079574639,
0, 0.958706250415071, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0.747797205162342, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.651913135519311,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.73485217216192, 0, 0, 0.275475340095472, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.18247806913975,
0.579953153217946, 0, 0, 0, 0, -0.00550535625446915, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.579953153217946, 1.01537514466963,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.275475340095472,
0, 0, 0.785695412105443), .Dim = c(20L, 20L),
.Dimnames = list(c("a2", "a5", "a7", "a9", "c3", "c4", "c8", "c9", "e1",
"e4", "e6", "e7", "n1", "n2", "n6", "n8", "i2", "i8",
"i9", "i10"),
c("a2", "a5", "a7", "a9", "c3", "c4", "c8",
"c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6", "n8",
"i2", "i8", "i9", "i10")),
class = c("lavaan.matrix.symmetric", "matrix")),
psi = structure(
c(0.561994064185727, -0.0358719479236162,
0.135253238440016, -0.159404773244813, 0.293918421161048,
-0.0358719479236162, 1.4549742724029, 0.114382670912166,
-0.309950522703722, -0.244829380643405, 0.135253238440016,
0.114382670912166, 0.979290499947525, -0.175364444285233,
0.454638527570875, -0.159404773244813, -0.309950522703722,
-0.175364444285233, 1.11370301060926, -0.0548613801146908,
0.293918421161048, -0.244829380643405, 0.454638527570875,
-0.0548613801146908, 1.85938365019618), .Dim = c(5L, 5L),
.Dimnames = list(
c("A", "C", "E", "N", "O"), c("A", "C", "E", "N", "O"
)), class = c("lavaan.matrix.symmetric", "matrix")),
nu = structure(
c(4.09824764469264, 3.56191664603162,
3.99887279416986, 3.61846568375092, 3.28727563899424,
4.26318382086251, 4.18115621522395, 3.59932137934746,
2.26973604341351, 2.92379355460568, 3.4278175784955,
3.09054924993737, 2.56642940207529, 2.69946144321671,
2.32370361993874, 2.27867084045946, 3.97168549581889,
3.59000455755382, 3.61505997818372, 4.07151827816703),
.Dim = c(20L, 1L),
.Dimnames = list(c("a2", "a5", "a7", "a9", "c3",
"c4", "c8", "c9", "e1", "e4", "e6", "e7", "n1", "n2",
"n6", "n8", "i2", "i8", "i9", "i10"), "intercept"),
class = c("lavaan.matrix",
"matrix")),
alpha = structure(
c(0.742530416810915, 0.140276996932641,
-0.0193402230099476, -0.0491017394271967, -0.458225607619261
), .Dim = c(5L, 1L),
.Dimnames = list(c("A", "C", "E", "N", "O"), "intercept"),
class = c("lavaan.matrix", "matrix")))),
class = c("lavaan.list", "list"))
# Create sample output
pimout_eq <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
weights_latent = c(0.0325, 0.1795, 0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = (result[[2]]$lambda + result[[1]]$lambda) / 2,
nu_r = (result[[2]]$nu + result[[1]]$nu) / 2,
Theta_r = (result[[2]]$theta + result[[1]]$theta) / 2
)
pimout <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
# Agreeableness Conscientiousness Extraversion Neuroticism Openness
weights_latent = c(0.0325, 0.1795, 0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
## test weights_latent is null
test_that("PartInv() runs with no latent weight input", {
pimout_latwei_null <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
pimout_latwei_ba <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
weights_latent = c(rep(1, 5)),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
expect_equal(pimout_latwei_ba[1:4], pimout_latwei_null[1:4])
})
## test weights_item is null
test_that("PartInv() runs with no item weight input", {
pimout_itwei_null <- PartInv(
propsel = .25,
weights_latent = c(0.0325, 0.1795,
0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
pimout_itwei_ba <- PartInv(
propsel = .25,
weights_item = c(rep(1, 20)),
weights_latent = c(0.0325, 0.1795,
0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
expect_equal(pimout_itwei_ba[1:4], pimout_itwei_null[1:4])
})
## test weights_item is fraction
test_that("PartInv() runs with no latent weight input", {
expect_warning(
pimout_latwei_null <- PartInv(
cut_z = 80,
weights_item = c(rep(1/3, 20)),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
),
"Proportion selected is 1% or less")
})
## test equivalence of two functions
test_that("PartInv() runs with no item weight input", {
pi_res_eq <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
weights_latent = c(0.0325, 0.1795,
0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
expect_equal(pi_res_eq[1:4], pimout[1:4])
})
# test labels changed
test_that("PartInvMulti_we with customized label", {
pimout_label <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
weights_latent = c(0.0325, 0.1795,
0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta,
labels = c("Female", "Male")
)
expect_identical(colnames(pimout_label[[4]]), c("Female", "Male", "E_R(Male)"))
})
claycantrell/PartInvShinyUI documentation built on March 29, 2022, 9:49 a.m.
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result <- structure(
list(`1` = list(
lambda = structure(
c(0.321851420828946,
0.65505328221763, 0.644928823284184, 0.745498551641102, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.569789973707324,
0.341398323887283, 0.397589912762831, 0.745400693889335, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.6572331474069,
0.803018980949713, 0.798604339572203, 0.685778873051152, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.50691173408154,
0.824339800976872, 0.599603442972015, 0.825307748488813, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.511822774613899,
0.425281197599131, 0.484803397473042, 0.569706848613303),
.Dim = c(20L, 5L),
.Dimnames = list(c("a2", "a5", "a7", "a9", "c3", "c4", "c8",
"c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6", "n8", "i2", "i8",
"i9", "i10"),
c("A", "C", "E", "N", "O")),
class = c("lavaan.matrix", "matrix")),
theta = structure(
c(0.543886582321731, 0.172041746020309,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0120358623284618, 0, 0, 0, 0, 0,
0, 0, 0, 0.172041746020309, 0.536443955046005, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.410358018613791,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.356096075938922,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.148959243230043,
0, 0, 0, 0, 0, 0.934929805416671, 0, 0, 0, 0, 0, -0.232254971317054,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.409621144057789,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.495104906416798,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.924828156814879,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.78444201074091,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.991446629333851,
0, -0.1069952336659, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.232254971317054,
0, 0, 0, 0, 0, 0.880871827235737, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.0120358623284618, 0, 0, 0, 0, 0, 0, 0, 0, -0.1069952336659,
0, 0.611527086912206, 0, -0.0226876197802865, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.66269941620454, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.0226876197802865,
0, 0.569648257556627, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.747797205162342, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.651913135519311, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.73485217216192,
0, 0, 0.312250352868153, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1.18247806913975, 0.457286841547525, 0, 0, 0,
0, 0.148959243230043, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.457286841547525, 1.01537514466963, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.312250352868153, 0, 0, 0.785695412105443
),
.Dim = c(20L, 20L),
.Dimnames = list(c("a2", "a5", "a7", "a9",
"c3", "c4", "c8", "c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6",
"n8", "i2", "i8", "i9", "i10"),
c("a2", "a5", "a7", "a9", "c3",
"c4", "c8", "c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6", "n8",
"i2", "i8", "i9", "i10")),
class = c("lavaan.matrix.symmetric", "matrix")),
psi = structure(
c(1, 0.0307300527642325, 0.397826036072362,
-0.190732145703416, 0.416212032411235, 0.0307300527642325, 1,
0.0516464797818452, -0.1590078212592, -0.00935598159738081, 0.397826036072362,
0.0516464797818452, 1, -0.0409034475100417, 0.672259531068557,
-0.190732145703416, -0.1590078212592, -0.0409034475100417, 1,
-0.0589307820291875, 0.416212032411235, -0.00935598159738081,
0.672259531068557, -0.0589307820291875, 1),
.Dim = c(5L, 5L),
.Dimnames = list(c("A", "C", "E", "N", "O"), c("A", "C", "E", "N", "O")),
class = c("lavaan.matrix.symmetric","matrix")),
nu = structure(
c(3.94424798096106, 3.56191664603162,
3.99887279416986, 3.61846568375092, 3.28727563899424, 4.26318382086251,
4.18115621522395, 3.59932137934746, 2.26973604341351, 2.92379355460568,
3.01186745338878, 3.09054924993737, 2.25941455787935, 2.46014063678953,
2.32370361993874, 2.27867084045946, 3.97168549581889, 3.59000455755382,
3.61505997818372, 4.07151827816703),
.Dim = c(20L, 1L),
.Dimnames = list(
c("a2", "a5", "a7", "a9", "c3", "c4", "c8", "c9", "e1", "e4",
"e6", "e7", "n1", "n2", "n6", "n8", "i2", "i8", "i9", "i10"
), "intercept"), class = c("lavaan.matrix", "matrix")),
alpha = structure(c(0, 0, 0, 0, 0),
.Dim = c(5L, 1L),
.Dimnames = list(c("A", "C", "E", "N", "O"), "intercept"),
class = c("lavaan.matrix", "matrix"))),
`2` = list(
lambda = structure(
c(0.321851420828946, 0.65505328221763,
0.644928823284185, 0.745498551641103, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.569789973707324,
0.341398323887284, 0.397589912762831, 0.745400693889336,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.6572331474069, 0.803018980949713, 0.798604339572203,
0.685778873051152, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.50691173408154, 0.824339800976872,
0.599603442972015, 0.825307748488813, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.511822774613899,
0.425281197599131, 0.484803397473042, 0.569706848613303),
.Dim = c(20L, 5L),
.Dimnames = list(c("a2", "a5", "a7", "a9", "c3", "c4",
"c8", "c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6", "n8",
"i2", "i8", "i9", "i10"),
c("A", "C", "E", "N", "O")),
class = c("lavaan.matrix", "matrix")),
theta = structure(
c(0.543886582321732, 0.0991628559089238,
0, 0, 0, 0, 0, 0, 0, 0, 0, -0.115517592631624, 0, 0, 0, 0,
0, 0, 0, 0, 0.0991628559089238, 0.536443955046005, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.410358018613791,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.356096075938922, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, -0.00550535625446915, 0, 0, 0, 0, 0, 0.934929805416671,
0, 0, 0, 0, 0, -0.0296478578193999, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.409621144057789, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.70483713633214,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.924828156814879, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0.78444201074091, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.991446629333851,
0, -0.082909427455581, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-0.0296478578193999, 0, 0, 0, 0, 0, 0.880871827235738, 0,
0, 0, 0, 0, 0, 0, 0, 0, -0.115517592631624, 0, 0, 0, 0, 0,
0, 0, 0, -0.082909427455581, 0, 0.611527086912206, 0, -0.146167079574639,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.943687415419278,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.146167079574639,
0, 0.958706250415071, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0.747797205162342, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.651913135519311,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.73485217216192, 0, 0, 0.275475340095472, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.18247806913975,
0.579953153217946, 0, 0, 0, 0, -0.00550535625446915, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.579953153217946, 1.01537514466963,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.275475340095472,
0, 0, 0.785695412105443), .Dim = c(20L, 20L),
.Dimnames = list(c("a2", "a5", "a7", "a9", "c3", "c4", "c8", "c9", "e1",
"e4", "e6", "e7", "n1", "n2", "n6", "n8", "i2", "i8",
"i9", "i10"),
c("a2", "a5", "a7", "a9", "c3", "c4", "c8",
"c9", "e1", "e4", "e6", "e7", "n1", "n2", "n6", "n8",
"i2", "i8", "i9", "i10")),
class = c("lavaan.matrix.symmetric", "matrix")),
psi = structure(
c(0.561994064185727, -0.0358719479236162,
0.135253238440016, -0.159404773244813, 0.293918421161048,
-0.0358719479236162, 1.4549742724029, 0.114382670912166,
-0.309950522703722, -0.244829380643405, 0.135253238440016,
0.114382670912166, 0.979290499947525, -0.175364444285233,
0.454638527570875, -0.159404773244813, -0.309950522703722,
-0.175364444285233, 1.11370301060926, -0.0548613801146908,
0.293918421161048, -0.244829380643405, 0.454638527570875,
-0.0548613801146908, 1.85938365019618), .Dim = c(5L, 5L),
.Dimnames = list(
c("A", "C", "E", "N", "O"), c("A", "C", "E", "N", "O"
)), class = c("lavaan.matrix.symmetric", "matrix")),
nu = structure(
c(4.09824764469264, 3.56191664603162,
3.99887279416986, 3.61846568375092, 3.28727563899424,
4.26318382086251, 4.18115621522395, 3.59932137934746,
2.26973604341351, 2.92379355460568, 3.4278175784955,
3.09054924993737, 2.56642940207529, 2.69946144321671,
2.32370361993874, 2.27867084045946, 3.97168549581889,
3.59000455755382, 3.61505997818372, 4.07151827816703),
.Dim = c(20L, 1L),
.Dimnames = list(c("a2", "a5", "a7", "a9", "c3",
"c4", "c8", "c9", "e1", "e4", "e6", "e7", "n1", "n2",
"n6", "n8", "i2", "i8", "i9", "i10"), "intercept"),
class = c("lavaan.matrix",
"matrix")),
alpha = structure(
c(0.742530416810915, 0.140276996932641,
-0.0193402230099476, -0.0491017394271967, -0.458225607619261
), .Dim = c(5L, 1L),
.Dimnames = list(c("A", "C", "E", "N", "O"), "intercept"),
class = c("lavaan.matrix", "matrix")))),
class = c("lavaan.list", "list"))
# Create sample output
pimout_eq <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
weights_latent = c(0.0325, 0.1795, 0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = (result[[2]]$lambda + result[[1]]$lambda) / 2,
nu_r = (result[[2]]$nu + result[[1]]$nu) / 2,
Theta_r = (result[[2]]$theta + result[[1]]$theta) / 2
)
pimout <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
# Agreeableness Conscientiousness Extraversion Neuroticism Openness
weights_latent = c(0.0325, 0.1795, 0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
## test weights_latent is null
test_that("PartInv() runs with no latent weight input", {
pimout_latwei_null <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
pimout_latwei_ba <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
weights_latent = c(rep(1, 5)),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
expect_equal(pimout_latwei_ba[1:4], pimout_latwei_null[1:4])
})
## test weights_item is null
test_that("PartInv() runs with no item weight input", {
pimout_itwei_null <- PartInv(
propsel = .25,
weights_latent = c(0.0325, 0.1795,
0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
pimout_itwei_ba <- PartInv(
propsel = .25,
weights_item = c(rep(1, 20)),
weights_latent = c(0.0325, 0.1795,
0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
expect_equal(pimout_itwei_ba[1:4], pimout_itwei_null[1:4])
})
## test weights_item is fraction
test_that("PartInv() runs with no latent weight input", {
expect_warning(
pimout_latwei_null <- PartInv(
cut_z = 80,
weights_item = c(rep(1/3, 20)),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
),
"Proportion selected is 1% or less")
})
## test equivalence of two functions
test_that("PartInv() runs with no item weight input", {
pi_res_eq <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
weights_latent = c(0.0325, 0.1795,
0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta
)
expect_equal(pi_res_eq[1:4], pimout[1:4])
})
# test labels changed
test_that("PartInvMulti_we with customized label", {
pimout_label <- PartInv(
propsel = .25,
weights_item = c(0.008125, 0.008125, 0.008125, 0.008125,
0.044875, 0.044875, 0.044875, 0.044875,
0.117325, 0.117325, 0.117325, 0.117325,
-0.048775, -0.048775, -0.048775, -0.048775,
0.0309, 0.0309, 0.0309, 0.0309),
weights_latent = c(0.0325, 0.1795,
0.4693, -0.1951, 0.1236),
alpha_r = result[[2]]$alpha,
alpha_f = result[[1]]$alpha,
psi_r = result[[2]]$psi,
psi_f = result[[1]]$psi,
lambda_r = result[[2]]$lambda,
nu_r = result[[2]]$nu,
nu_f = result[[1]]$nu,
Theta_r = result[[2]]$theta,
Theta_f = result[[1]]$theta,
labels = c("Female", "Male")
)
expect_identical(colnames(pimout_label[[4]]), c("Female", "Male", "E_R(Male)"))
})
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