I'm trying to fit a propensity score weighted logistic regression model with PSweight package. My dataset contains clusters defined by the "ID" variable therefore I ran the "_cl" alternatives.
First, I defined the PS formula
ps.any_cl<-Gruppo Age+Sex+SpO2+FC+PAS1+GCS+Sincope+EPA+Primo_episodio+antiaritmici+PTCA_BPAC+Pat_congenita+(1|ID)
then I tried to evaluate the balance obtained with the different weighting modalities:
bal.any_cl <- SumStat_cl(ps.formula = ps.any_cl, data = data, weight=c("overlap")
This is the error I'm obtaining:
boundary (singular) fit: see help('isSingular') Error in dimnames(x) <- dn : length of 'dimnames' [1] not equal to array extent
`
Of note, I do not obtain any error if I use the non-cluster options of the PSweight package
Moreover,if I try to fit the model also considering clusters, I have no problems with that
ato.any_cl<-PSweight_cl(
ps.formula = ps.any_cl,
yname="Esito",
data=data,
weight = "overlap",
delta = 0,
augmentation = FALSE,
bootstrap = FALSE,
bs_level = NULL,
R = 50,
out.formula = NULL,
family = "binomial",
nAGQ = 1L
)
summary(ato.any_cl)
`Closed-form inference:
Original group value: 0, 1
Contrast: 0 1 Contrast 1 -1 1
Estimate Std.Error lwr upr Pr(>|z|)
Contrast 1 0.123066 0.095590 -0.064288 0.31042 0.1979`
I've tried:
- simplyfing the variables in the PS by removing one by one but I always receive the same error
- building a cluster PS with the "psdata_cl" dataset obtained with the PSweight package and it worked, but I could not find a solution for my data.
Have you got any ideas?
Thank you in advance
Lorenzo