search for: lmermodlmertest

Displaying 4 results from an estimated 4 matches for "lmermodlmertest".

lmer error: number of observations <= number of random effects
2024 May 05
2
lmer error: number of observations <= number of random effects
...data = LSIDATA, control = lmerControl(check.nobs.vs.nRE = "ignore", optimizer ="bobyqa", check.conv.singular = .makeCC(action = "ignore", tol = 1e-4)), REML=TRUE) summary(modelLSI_maineff_RE) Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest'] Formula: SA ~ Index1 * LSI + (1 + Index1 + LSI | ID) Data: LSIDATA Control: lmerControl(check.nobs.vs.nRE = "ignore", optimizer = "bobyqa", check.conv.singular = .makeCC(action = "ignore", tol = 1e-04)) REML criterion at convergence: 7299.6 Scaled residuals: Mi...
lmer error: number of observations <= number of random effects
2024 May 05
2
lmer error: number of observations <= number of random effects
...data = LSIDATA, control = lmerControl(check.nobs.vs.nRE = "ignore", optimizer ="bobyqa", check.conv.singular = .makeCC(action = "ignore", tol = 1e-4)), REML=TRUE) summary(modelLSI_maineff_RE) Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest'] Formula: SA ~ Index1 * LSI + (1 + Index1 + LSI | ID) Data: LSIDATA Control: lmerControl(check.nobs.vs.nRE = "ignore", optimizer = "bobyqa", check.conv.singular = .makeCC(action = "ignore", tol = 1e-04)) REML criterion at convergence: 7299.6 Scaled residuals: Mi...
[R-sig-ME] lmer error: number of observations <= number of random effects
2024 May 06
0
[R-sig-ME] lmer error: number of observations <= number of random effects
...rControl(check.nobs.vs.nRE = > "ignore", optimizer ="bobyqa", check.conv.singular = .makeCC(action = > "ignore", tol = 1e-4)), REML=TRUE) > > summary(modelLSI_maineff_RE) > Linear mixed model fit by REML. t-tests use Satterthwaite's method > ['lmerModLmerTest'] > Formula: SA ~ Index1 * LSI + (1 + Index1 + LSI | ID) > Data: LSIDATA > Control: lmerControl(check.nobs.vs.nRE = "ignore", optimizer = "bobyqa", > check.conv.singular = .makeCC(action = "ignore", tol = 1e-04)) > > REML criterion at convergence:...
[R] [R-sig-ME] lmer error: number of observations <= number of random effects
2024 May 06
0
[R] [R-sig-ME] lmer error: number of observations <= number of random effects
...rControl(check.nobs.vs.nRE = > "ignore", optimizer ="bobyqa", check.conv.singular = .makeCC(action = > "ignore", tol = 1e-4)), REML=TRUE) > > summary(modelLSI_maineff_RE) > Linear mixed model fit by REML. t-tests use Satterthwaite's method > ['lmerModLmerTest'] > Formula: SA ~ Index1 * LSI + (1 + Index1 + LSI | ID) > Data: LSIDATA > Control: lmerControl(check.nobs.vs.nRE = "ignore", optimizer = "bobyqa", > check.conv.singular = .makeCC(action = "ignore", tol = 1e-04)) > > REML criterion at convergence:...