Displaying 4 results from an estimated 4 matches for "feidt".
2024 May 05
2
lmer error: number of observations <= number of random effects
...dom effects (=1479)
for term (1 + Index1 + LSI | ID); the random-effects parameters and the
residual variance (or scale parameter) are probably unidentifiable
I did test the within-person variance for the LSI variable and the
within-person variance is significant from the Greenhouse-Geisser,
Hyunh-Feidt tests.
I also tried control = lmerControl(check.nobs.vs.nRE = "ignore") which gave
me the following output. modelLSI_maineff_RE <- lmer(SA ~ Index1* LSI+ (1 +
Index1+LSI |ID), data = LSIDATA, control = lmerControl(check.nobs.vs.nRE =
"ignore", optimizer ="bobyqa",...
2024 May 05
2
lmer error: number of observations <= number of random effects
...dom effects (=1479)
for term (1 + Index1 + LSI | ID); the random-effects parameters and the
residual variance (or scale parameter) are probably unidentifiable
I did test the within-person variance for the LSI variable and the
within-person variance is significant from the Greenhouse-Geisser,
Hyunh-Feidt tests.
I also tried control = lmerControl(check.nobs.vs.nRE = "ignore") which gave
me the following output. modelLSI_maineff_RE <- lmer(SA ~ Index1* LSI+ (1 +
Index1+LSI |ID), data = LSIDATA, control = lmerControl(check.nobs.vs.nRE =
"ignore", optimizer ="bobyqa",...
2024 May 06
0
[R-sig-ME] lmer error: number of observations <= number of random effects
...term (1 + Index1 + LSI | ID); the random-effects parameters and the
> residual variance (or scale parameter) are probably unidentifiable
>
> I did test the within-person variance for the LSI variable and the
> within-person variance is significant from the Greenhouse-Geisser,
> Hyunh-Feidt tests.
>
> I also tried control = lmerControl(check.nobs.vs.nRE = "ignore") which gave
> me the following output. modelLSI_maineff_RE <- lmer(SA ~ Index1* LSI+ (1 +
> Index1+LSI |ID), data = LSIDATA, control = lmerControl(check.nobs.vs.nRE =
> "ignore", optimiz...
2024 May 06
0
[R] [R-sig-ME] lmer error: number of observations <= number of random effects
...term (1 + Index1 + LSI | ID); the random-effects parameters and the
> residual variance (or scale parameter) are probably unidentifiable
>
> I did test the within-person variance for the LSI variable and the
> within-person variance is significant from the Greenhouse-Geisser,
> Hyunh-Feidt tests.
>
> I also tried control = lmerControl(check.nobs.vs.nRE = "ignore") which gave
> me the following output. modelLSI_maineff_RE <- lmer(SA ~ Index1* LSI+ (1 +
> Index1+LSI |ID), data = LSIDATA, control = lmerControl(check.nobs.vs.nRE =
> "ignore", optimiz...