# How to interpret the negative variances

Cross Validated Asked by Aakash Bashyal on December 12, 2020

I had used the already published Likert scale for the survey. And the responses to the survey from 98 participants were collected. The survey likert scale was from 1-5 from strongly diasgree to srongle agree.

Looking at the variables the average value of one of the factors is above the 3 for all the questions. The figure below is the avg of the responses.

But while evaluating the variances the estimate, std.lv are valued seems to be negatives.

                  Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all

.Competence       -0.188    0.105   -1.796    0.073   -0.324   -0.324


and it is giving the warning:

lavaan WARNING: some estimated lv variances are negative


Model i am using:

model <- '
Competence =~ COMP1 + COMP2 + COMP3 + COMP4
Autonomy =~  AUT1 + AUT2 + AUT3
Relatedness =~ REL1 + REL2 + REL3 + REL4
Motivation =~ Autonomy + Relatedness + Competence

Vigor =~ VIGOR1 + VIGOR2 + VIGOR3  +VIGOR4 + VIGOR5
Dedication =~ DED1 +DED2 +DED3 +DED4 +DED5
Absorption =~ ABS1 +ABS2 +ABS3 +ABS4
Engagement =~ Vigor + Dedication + Absorption

Motivation ~~ Engagement

'

fit <- sem(model,data = Log_And_SurveyResult)

summary(fit, standardized=T)


However, what these variables predict appears to be significant with other variables i.e Motivation and Engagement seems to be co-related.

Now, due to the value of negative in the estimate, I am confused about how to interpret the result?

I can add further information if need to answer the question.

Also, in the output of the LavaanPlot, the loadings are high.

I am stuck in the interpretation for many days. Any help will be appreciated.

Thank you.

## One Answer

There may be a few issues going on. The first thing that comes to me is that perhaps your estimator is incorrect. It looks like you've used the default maximum likelihood estimator, but this has some specific assumptions that may not be met with Likert scales. You may check using the WLMSV estimator instead. Also, it looks like you're doing a factor analysis on the scale, so instead of calling sem() you might just want to use cfa(). It shouldn't affect your results a lot, but the cfa() function has some useful default arguments for when the goal is just a factor analysis.

Some other issues that you might want to consider is that your sample is too small and/or that there is too much collinearity in the data. I'm not terribly surprised by finding a Heywood case in this model since you're fitting a hierarchical factor analysis on just 98 people. I'd just go through some assumption checking if an alternative estimator doesn't fix the problem.

Another possible issue is just that the model is misspecified. You might consider exploratory factor analysis and see if that results in some better behaved models if nothing else works.

Answered by Billy on December 12, 2020

## Related Questions

### R: When do we use mean or median for the y axis in ggplot2 when doing analysis on property prices?

0  Asked on January 28, 2021 by chua-s-yang

### COCO evaluation – Negative values on AP and AR

0  Asked on January 28, 2021 by visionenthusiast

### How to make the regressor of LASSO consistent?

0  Asked on January 28, 2021 by zqq

### Suggestions for identifying the most “important” image labels

1  Asked on January 28, 2021 by nlapidot

### Any ideas on how to segment a 2D vector field?

0  Asked on January 28, 2021 by tricostume

### Binomial logistic regression for multiclass problems

1  Asked on January 27, 2021 by mathews24

### How is confidence defined in Expected Calibration Error?

0  Asked on January 26, 2021 by thecity2

### Why does the McNemar’s test use $chi^{2}$ and not the normal distribution?

2  Asked on January 26, 2021

### What algorithm can you use if you want clusters but only are interested in one group?

0  Asked on January 26, 2021 by bonesones

### Can I use an unknown number of variables to model my time-series?

0  Asked on January 26, 2021 by kplauritzen

### Variance of a stationary AR(2) model

2  Asked on January 26, 2021 by user369210

### Avoiding adjustments for time-varying controls in difference-in-differences (DID)?

0  Asked on January 26, 2021

### Removing the effect from structural breaks

1  Asked on January 25, 2021 by kiril-e-proykov

### Recommender System – Predict ratings with Random Forest Regressor or Classifier?

0  Asked on January 24, 2021 by oja-niva

### Nonparametric assessment of multiple predictors

0  Asked on January 24, 2021 by mephisto73

### Calculating measurement variance to achieve desired accuracy in estimation

0  Asked on January 23, 2021 by valjean

### Can large # of epochs or smaller batchsize compensate for smaller data size in training lstms

1  Asked on January 23, 2021 by tjt

### Probability that number of heads exceeds sum of die rolls

5  Asked on January 23, 2021 by user239903

### Combining Sub-Samples for Factor Analysis?

0  Asked on January 22, 2021

### Need to create a model to identify patterns in user details

0  Asked on January 21, 2021 by pooza

### Ask a Question

Get help from others!

© 2022 AnswerBun.com. All rights reserved. Sites we Love: PCI Database, MenuIva, UKBizDB, Menu Kuliner, Sharing RPP, SolveDir