Infinite values error calculating weights using ipw
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I am attempting to estimate a set of stabilized inverse probability weights for a propensity score model using the ipw package in R. I have a dataframe with 34517 observations, of which, 155 are in my treatment group.
mfg_stabilized_full <- ipwpoint(exposure = pmd_dummy, family = "binomial", link = "logit",
numerator = ~1,
denominator = ~ mfgshare + owner_per + dist_km + network_density,
data = city_lehd_acs04)
When running, I get an error message saying there are NAs in the weights. When I attempt to calculate unstabilized weights by removing the numerator term from ipwpoint() the weights that are returned are infinite.
In both calls the underlying logistic models converge and return estimates for each of the covariates. Considering that the underlying logistic model completes, why would I continue to get infinite values for unstabilized weights and NAs for stabilized?
r
asked May 21 at 0:47
elmuertefurioso
1487
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I am attempting to estimate a set of stabilized inverse probability weights for a propensity score model using the ipw package in R. I have a dataframe with 34517 observations, of which, 155 are in my treatment group.
mfg_stabilized_full <- ipwpoint(exposure = pmd_dummy, family = "binomial", link = "logit",
numerator = ~1,
denominator = ~ mfgshare + owner_per + dist_km + network_density,
data = city_lehd_acs04)
When running, I get an error message saying there are NAs in the weights. When I attempt to calculate unstabilized weights by removing the numerator term from ipwpoint() the weights that are returned are infinite.
In both calls the underlying logistic models converge and return estimates for each of the covariates. Considering that the underlying logistic model completes, why would I continue to get infinite values for unstabilized weights and NAs for stabilized?
r
asked May 21 at 0:47
elmuertefurioso
1487
Are some of the probabilities zero?
– G5W
May 21 at 0:55
When I ran a summary on the fitted values the min was above zero. Far as I know there are none.
– elmuertefurioso
May 22 at 6:42
Try using theWeightItpackage. For simple cases like this, it does the same thing asipwbut has clearer syntax and errors.
– Noah
Jun 27 at 21:11
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I am attempting to estimate a set of stabilized inverse probability weights for a propensity score model using the ipw package in R. I have a dataframe with 34517 observations, of which, 155 are in my treatment group.
mfg_stabilized_full <- ipwpoint(exposure = pmd_dummy, family = "binomial", link = "logit",
numerator = ~1,
denominator = ~ mfgshare + owner_per + dist_km + network_density,
data = city_lehd_acs04)
When running, I get an error message saying there are NAs in the weights. When I attempt to calculate unstabilized weights by removing the numerator term from ipwpoint() the weights that are returned are infinite.
In both calls the underlying logistic models converge and return estimates for each of the covariates. Considering that the underlying logistic model completes, why would I continue to get infinite values for unstabilized weights and NAs for stabilized?
r
asked May 21 at 0:47
elmuertefurioso
1487
I am attempting to estimate a set of stabilized inverse probability weights for a propensity score model using the ipw package in R. I have a dataframe with 34517 observations, of which, 155 are in my treatment group.
mfg_stabilized_full <- ipwpoint(exposure = pmd_dummy, family = "binomial", link = "logit",
numerator = ~1,
denominator = ~ mfgshare + owner_per + dist_km + network_density,
data = city_lehd_acs04)
When running, I get an error message saying there are NAs in the weights. When I attempt to calculate unstabilized weights by removing the numerator term from ipwpoint() the weights that are returned are infinite.
In both calls the underlying logistic models converge and return estimates for each of the covariates. Considering that the underlying logistic model completes, why would I continue to get infinite values for unstabilized weights and NAs for stabilized?
r
r
asked May 21 at 0:47
elmuertefurioso
1487
asked May 21 at 0:47
elmuertefurioso
1487
asked May 21 at 0:47
elmuertefurioso
1487
asked May 21 at 0:47
elmuertefurioso
1487
asked May 21 at 0:47
elmuertefurioso
1487
1487
Are some of the probabilities zero?
– G5W
May 21 at 0:55
When I ran a summary on the fitted values the min was above zero. Far as I know there are none.
– elmuertefurioso
May 22 at 6:42
Try using theWeightItpackage. For simple cases like this, it does the same thing asipwbut has clearer syntax and errors.
– Noah
Jun 27 at 21:11
add a comment |
Are some of the probabilities zero?
– G5W
May 21 at 0:55
When I ran a summary on the fitted values the min was above zero. Far as I know there are none.
– elmuertefurioso
May 22 at 6:42
Try using theWeightItpackage. For simple cases like this, it does the same thing asipwbut has clearer syntax and errors.
– Noah
Jun 27 at 21:11
Are some of the probabilities zero?
– G5W
May 21 at 0:55
Are some of the probabilities zero?
– G5W
May 21 at 0:55
When I ran a summary on the fitted values the min was above zero. Far as I know there are none.
– elmuertefurioso
May 22 at 6:42
When I ran a summary on the fitted values the min was above zero. Far as I know there are none.
– elmuertefurioso
May 22 at 6:42
Try using the
WeightIt package. For simple cases like this, it does the same thing as ipw but has clearer syntax and errors.– Noah
Jun 27 at 21:11
Try using the
WeightIt package. For simple cases like this, it does the same thing as ipw but has clearer syntax and errors.– Noah
Jun 27 at 21:11
add a comment |
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Check your exposure coding. A binary exposure should be coded as 0 and 1 as per the package manual. I ran into the same error when my exposure was coded as a factor.
answered Nov 12 at 18:12
Stefan
1
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1 Answer
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up vote
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Check your exposure coding. A binary exposure should be coded as 0 and 1 as per the package manual. I ran into the same error when my exposure was coded as a factor.
answered Nov 12 at 18:12
Stefan
1
add a comment |
up vote
0
down vote
Check your exposure coding. A binary exposure should be coded as 0 and 1 as per the package manual. I ran into the same error when my exposure was coded as a factor.
answered Nov 12 at 18:12
Stefan
1
add a comment |
up vote
0
down vote
up vote
0
down vote
Check your exposure coding. A binary exposure should be coded as 0 and 1 as per the package manual. I ran into the same error when my exposure was coded as a factor.
answered Nov 12 at 18:12
Stefan
1
Check your exposure coding. A binary exposure should be coded as 0 and 1 as per the package manual. I ran into the same error when my exposure was coded as a factor.
answered Nov 12 at 18:12
Stefan
1
answered Nov 12 at 18:12
Stefan
1
answered Nov 12 at 18:12
Stefan
1
answered Nov 12 at 18:12
Stefan
1
1
add a comment |
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Are some of the probabilities zero?
– G5W
May 21 at 0:55
When I ran a summary on the fitted values the min was above zero. Far as I know there are none.
– elmuertefurioso
May 22 at 6:42
Try using the
WeightItpackage. For simple cases like this, it does the same thing asipwbut has clearer syntax and errors.– Noah
Jun 27 at 21:11