"variable lengths differ" error while running regressions in a loop

Question

I am trying to run a regression loop based on code that I have found in a previous answer (How to Loop/Repeat a Linear Regression in R) but I keep getting an error. My outcomes (dependent) are 940 variables (metabolites) and my exposure (independent) are "bmi","Age", "sex","lpa2c", and "smoking". where BMI and Age are continuous. BMI is the mean exposure, and for others, I am controlling for them. So I'm testing the effect of BMI on 940 metabolites. Also, I would like to know how I can extract coefficient, p-value, standard error, and confidence interval for BMI only and when it is significant.

This is the code I have used:

y<- c(1653:2592) # response 
x1<- c("bmi","Age", "sex","lpa2c", "smoking") # predictor 

for (i in x1){ 
  model <- lm(paste("y ~", i[[1]]), data= QBB_clean) 
  print(summary(model)) 
}

And this is the error:

Error in model.frame.default(formula = paste("y ~", i[[1]]), data = QBB_clean, : variable lengths differ (found for 'bmi').

              y1         y2          y3          y4 bmi age sex       lpa2c smoking
1   0.2875775201 0.59998896 0.238726027 0.784575267  24  18   1 0.470681834       1
2   0.7883051354 0.33282354 0.962358936 0.009429905  12  20   0 0.365845473       1
3   0.4089769218 0.48861303 0.601365726 0.779065883  18  15   0 0.121272054       0
4   0.8830174040 0.95447383 0.515029727 0.729390652  16  21   0 0.046993681       0
5   0.9404672843 0.48290240 0.402573342 0.630131853  18  28   1 0.262796304       1
6   0.0455564994 0.89035022 0.880246541 0.480910830  13  13   0 0.968641168       1
7   0.5281054880 0.91443819 0.364091865 0.156636851  11  12   0 0.488495482       1
8   0.8924190444 0.60873498 0.288239281 0.008215520  21  23   0 0.477822030       0
9   0.5514350145 0.41068978 0.170645235 0.452458394  18  17   1 0.748792881       0
10  0.4566147353 0.14709469 0.172171746 0.492293329  20  15   1 0.667640231       1

Ben Bolker · Accepted Answer · 2023-02-14T14:55:40.943

If you want to loop over responses you will want something like this:

respvars <- names(QBB_clean[1653:2592]) 
predvars <- c("bmi","Age", "sex","lpa2c", "smoking")
results <- list()
for (v in respvars) { 
  form <- reformulate(predvars, response = v)
  results[[v]] <- lm(form, data = QBB_clean)
}

You can then print the results with something like lapply(results, summary), extract coefficients, etc.. (I have a little trouble seeing how it's going to be useful to just print the results of 940 regressions ... are you really going to inspect them all?

If you want coefficients etc. for BMI, I think this should work (not tested):

t(sapply(results, function(m) coef(summary(m))["bmi",]))

Or for coefficients:

t(sapply(results, function(m) confint(m)["bmi",]))

"variable lengths differ" error while running regressions in a loop

1 Answers1