Groups
Conversations
All groups and messages
Send feedback to Google
Help
Sign in
Groups
lavaan
Conversations
Labels
2PL
2star
AMOS
CFA
CHOICE
CI
CSV
ClinicalRelevance
DFM
DIF
DISCRETE
DSEM
Fix
Hayes
Heywood
ICLV
ILD
IRT
LCSM
LGC
LGCM
LGM
LISREL
LS-model
Longitudinal
MIMIC
ML
MLM
MLR
Markdown
Mplus
NA
Output
RDSEM
RICLPM
Robusterror
SE
Second
Teresa
WLS
WLSMV
WRMR
Yuan-Bentler
absolutevalue
accuracy
aic
analysis
announcement
announement
arrays
autoregression
auxiliary
beta
between-cluster
bi-factor
bic2
bifactor
binary
binomial
blavaan
bootstrap
bug
categorical
cfi
change
check
chisq
clpm
clustering
cmv-in-lavaan
code
coefficient
commonmethodbias
composite
conditional
confirmatory
constraint
constraints
continuous-variables
controls
cor2cov
corrected
correction
correlation
correlationMatrix
corrrelations
count
covariance
covarianceMatrix
cross-lagged
cross-loading
curve
data
definite
dem
df
dichotomous
dichotomous_iv
dichotomous_outcome
dichtomic
difference
dignostics
directeffect
documentation
dummy_variable
dynr
effect
effects-coding
eiv
endogenous
eq
equalityconstraint
equation
error
error-in-variables
estfun
estimator
exogenous
explained
extraction
factor
factor-score
factorloading
factormean
feature
fiml
fit
fitMeasures
fitindices
fitted
fmi
freeing
fscore
fsr
general
getCov
group
groupmean
groups
growth
higher-order
identification
impact
imputation
imputed
included
indices
indirect
information-matrix
inspect
install_lavaan
installation
interaction
intercept
interpretation
interval
invariance
inverted
latent
latent-error
lavCor
lavPredict
lavTable
lavTestLRT
lavTestscore
lav_data_full
lav_model_objective
lavaan
lavaan-and-amos
lavtech
lbug
lcm
level2
linear
loading
logistic
logistic_regression
logit
loop
masem
mean
meancentering
measEqsyntax
measurement
measurement-error
measures
mediation
mediator
metric
mice_runMI
mipowerfit
missing
missingdata
missings
mixed
mixture
model
model-comparison
model-fit
modeling
moderated
moderated_mediation
moderation
moderator
modification
modifier
modindices
montecarlomed
mplus2lavaan
multi-imputed
multicollinearity
multidimensional
multigroup
multilevel
multiple
negating
negative
negativevariance
nested
nlminb
non-conformable
non-convergence
non-nested
noninvariance
nothing
observed
odds
odds_ratio
optimization
order
ordered
ordinal
originalData
overfitting
p-value
pairwise
parameter
partial
partial-regression
partially
path
path_coefficients
pathmodel
percentage
pipes
plotProbe
plots
pointEstimates
poisson
polynomial
positive
post-hoc
power
pre
predict
predictedprobability
predictions
predictor
probe2WayMC
probit
probit-regression
pseudo-R-squared
psych
python
r
r2
random
ratio
regression
release
reliability
repeated
reproducibility
residual
respone
ri-clpm
rlang
rmsea
robust
rpy2
rstudio
runMI
sample
satorra-bentler
saturatedmodel
scalar
scale
score
second-order
sem
semTools
sensitivity
sequential
significance
simsem
simulation
skew
slack
slope
small
smallsamplesize
srmr
standard-errors
standardized
strict
structural
subscript
summary
survey
survival
syntax
table
test-statistics
threshold
time
tutorial
tvc
varTable
variables
variance
visualizing
voung-test
vuongtest
warning
weighting
weights
within-cluster
workshops
z-score
رس
About
lavaan
1–5 of 4348
Welcome to the lavaan discussion group. Lavaan is an R package for latent variable analysis.
Mark all as read
Report abusive group
0 selected
Danushika Sivanathan
,
Terrence Jorgensen
3
6/30/20
Estimated LV variances negative for first order factor (with two factors predicting a second order factor)
Hi Terence, That is my mistake. I used the colon as a short hand. But the actual model is below: mode
unread,
Heywood
error
loading
negative
negativevariance
second-order
Estimated LV variances negative for first order factor (with two factors predicting a second order factor)
Hi Terence, That is my mistake. I used the colon as a short hand. But the actual model is below: mode
6/30/20
Burt Hatch
, …
Terrence Jorgensen
15
2/27/20
Heywood case with negative variance and calculation of CI with multiple imputations
Sorry for the confusion. Using cfa() I get nonconvergence. Using lavaan() I just get the heywood case
unread,
CFA
CI
Heywood
bifactor
error
negative
Heywood case with negative variance and calculation of CI with multiple imputations
Sorry for the confusion. Using cfa() I get nonconvergence. Using lavaan() I just get the heywood case
2/27/20
Dai Duong
, …
Edward Rigdon
4
6/15/19
Negative factor loading and Different estimated factor score vs Mplus
To nick Judd, fit is acceptable. CFI .962, TLI .953, RMSEA .051, SRMR .087 On Saturday, 15 June 2019
unread,
Mplus
factor-score
lavaan
loading
negative
Negative factor loading and Different estimated factor score vs Mplus
To nick Judd, fit is acceptable. CFI .962, TLI .953, RMSEA .051, SRMR .087 On Saturday, 15 June 2019
6/15/19
Ilse Coolen
,
Terrence Jorgensen
3
2/5/19
negative loading of single indicator in CFA
Hi Terrence, Thank you for taking the time to answer my questions. I just have a final question on
unread,
CFA
negative
negative loading of single indicator in CFA
Hi Terrence, Thank you for taking the time to answer my questions. I just have a final question on
2/5/19
Terrence Jorgensen
2
1/30/19
Re: Bug with warning messages?
It's possible that lavaan internally sets warn=FALSE when bootstrapping so that 1000 copies of
unread,
LGM
error
negative
positive
warning
Re: Bug with warning messages?
It's possible that lavaan internally sets warn=FALSE when bootstrapping so that 1000 copies of
1/30/19
Search
Clear search
Close search
Google apps
Main menu