r – Error in model.frame.default: variable lengths differ

r – Error in model.frame.default: variable lengths differ

Joran suggested to first remove the NAs before running the model. Thus, I removed the NAs, run the model and obtained the residuals. When I updated model2 by inclusion of the lagged residuals, the error message did not appear again.

Remove NAs

df2<-df1[complete.cases(df1),]

Run the main model

model2<-gam(death ~ pm10 + s(trend,k=14*7)+ s(temp,k=5), data=df2, family=poisson)

Obtain residuals

resid2 <- residuals(model2,type=deviance)

Update model2 by including the lag 1 residuals

model2_1 <- update(model2,.~.+ Lag(resid2,1),  na.action=na.omit)

Another thing that can cause this error is creating a model with the centering/scaling standardize function from the arm package — m <- standardize(lm(y ~ x, data = train))

If you then try predict(m), you get the same error as in this question.

r – Error in model.frame.default: variable lengths differ

Its simple, just make sure the data type in your columns are the same. For e.g. I faced the same error, that and an another error:

Error in contrasts<-(*tmp*, value = contr.funs[1 + isOF[nn]]) :
contrasts can be applied only to factors with 2 or more levels

So, I went back to my excel file or csv file, set a filter on the variable throwing me an error and checked if the distinct datatypes are the same. And… Oh! it had numbers and strings, so I converted numbers to string and it worked just fine for me.