Skip to main content
added 12 characters in body; edited tags
Source Link
kjetil b halvorsen
  • 82.8k
  • 32
  • 201
  • 663

I need to fit logistic regression models to a dataset where infection (present/absent) is my dependent variable and neighborhood (three factors: Rich, Poor, Very Poor) my independent variable.

According to a reviewer who (as I) is not well versed in stats, one potential problem with my data is that the variable neighborhood has a quite unevenly distributed sample size for each factor, such that:

Rich = 853
Poor = 100
Very poor = 131

Rich = 853  
Poor = 100  
Very poor = 131

The reviewer suggested randomly subsetting the "Rich" group to get a sample of about 100 samples and then meet this alleged assumption of approximately equal sample sizes between groups within the same variable.

Because of the hypothesis behind our study, I need to set "Rich" as the reference category against which to compare the remaining two.

Is the reviewer's suggestion founded? AFAIK, there's no violation of assumption whatsoever in logistic regression if the two categories of the independent variable are unbalanced, or even sparse, and no violation assumption even if it's the dependent variable.

I need to fit logistic regression models to a dataset where infection (present/absent) is my dependent variable and neighborhood (three factors: Rich, Poor, Very Poor) my independent variable.

According to a reviewer who (as I) is not well versed in stats, one potential problem with my data is that the variable neighborhood has a quite unevenly distributed sample size for each factor, such that:

Rich = 853
Poor = 100
Very poor = 131

The reviewer suggested randomly subsetting the "Rich" group to get a sample of about 100 samples and then meet this alleged assumption of approximately equal sample sizes between groups within the same variable.

Because of the hypothesis behind our study, I need to set "Rich" as the reference category against which to compare the remaining two.

Is the reviewer's suggestion founded? AFAIK, there's no violation of assumption whatsoever in logistic regression if the two categories of the independent variable are unbalanced, or even sparse, and no violation assumption even if it's the dependent variable.

I need to fit logistic regression models to a dataset where infection (present/absent) is my dependent variable and neighborhood (three factors: Rich, Poor, Very Poor) my independent variable.

According to a reviewer who (as I) is not well versed in stats, one potential problem with my data is that the variable neighborhood has a quite unevenly distributed sample size for each factor, such that:

Rich = 853  
Poor = 100  
Very poor = 131

The reviewer suggested randomly subsetting the "Rich" group to get a sample of about 100 samples and then meet this alleged assumption of approximately equal sample sizes between groups within the same variable.

Because of the hypothesis behind our study, I need to set "Rich" as the reference category against which to compare the remaining two.

Is the reviewer's suggestion founded? AFAIK, there's no violation of assumption whatsoever in logistic regression if the two categories of the independent variable are unbalanced, or even sparse, and no violation assumption even if it's the dependent variable.

edited tags
Link
kjetil b halvorsen
  • 82.8k
  • 32
  • 201
  • 663
Post Reopened by gung - Reinstate Monica, Sean Easter, mdewey, John, Matt Krause
Post Closed as "Duplicate" by kjetil b halvorsen, Peter Flom
Tweeted twitter.com/#!/StackStats/status/410483688053694466
deleted 77 characters in body; edited title
Source Link
Luciano
  • 649
  • 2
  • 9
  • 12

Unbalanced distribution of sample size between groups in logistic rergessionregression: should one worry?

I need to fit logistic regression models to a dataset where infection (present/absent) is my dependent variable and neighborhood (three factors: Rich, Poor, Very Poor) my independent variable.

According to a reviewer who (as I) is not well versed in stats, one potential problem with my data is that the variable neighborhood has a quite unevenly distributed sample size for each factor, such that:

Rich = 853
Poor = 100
Very poor = 131

The reviewer suggested randomly subsetting the "Rich" group to get a sample of about 100 samples and then meet this alleged assumption of approximately equal sample sizes between groups within the same variable.

Because of the hypotesishypothesis behind our study, I need to set "Rich" as the reference category against which to compare the remaining two.

Is the reviewer's suggestion founded? AFAIK, there's no violation of assumption whatsoever in logistic regression if the two categories of the independent variable are unbalanced, or even sparse, and no violation assumption even if it's the dependent variable.

I thank in advance any tips regarding this issue.

Cheers,

Luciano

Unbalanced distribution of sample size between groups in logistic rergession: should one worry?

I need to fit logistic regression models to a dataset where infection (present/absent) is my dependent variable and neighborhood (three factors: Rich, Poor, Very Poor) my independent variable.

According to a reviewer who (as I) is not well versed in stats, one potential problem with my data is that the variable neighborhood has a quite unevenly distributed sample size for each factor, such that:

Rich = 853
Poor = 100
Very poor = 131

The reviewer suggested randomly subsetting the "Rich" group to get a sample of about 100 samples and then meet this alleged assumption of approximately equal sample sizes between groups within the same variable.

Because of the hypotesis behind our study, I need to set "Rich" as the reference category against which to compare the remaining two.

Is the reviewer's suggestion founded? AFAIK, there's no violation of assumption whatsoever in logistic regression if the two categories of the independent variable are unbalanced, or even sparse, and no violation assumption even if it's the dependent variable.

I thank in advance any tips regarding this issue.

Cheers,

Luciano

Unbalanced distribution of sample size between groups in logistic regression: should one worry?

I need to fit logistic regression models to a dataset where infection (present/absent) is my dependent variable and neighborhood (three factors: Rich, Poor, Very Poor) my independent variable.

According to a reviewer who (as I) is not well versed in stats, one potential problem with my data is that the variable neighborhood has a quite unevenly distributed sample size for each factor, such that:

Rich = 853
Poor = 100
Very poor = 131

The reviewer suggested randomly subsetting the "Rich" group to get a sample of about 100 samples and then meet this alleged assumption of approximately equal sample sizes between groups within the same variable.

Because of the hypothesis behind our study, I need to set "Rich" as the reference category against which to compare the remaining two.

Is the reviewer's suggestion founded? AFAIK, there's no violation of assumption whatsoever in logistic regression if the two categories of the independent variable are unbalanced, or even sparse, and no violation assumption even if it's the dependent variable.

Rollback to Revision 1
Source Link
Luciano
  • 649
  • 2
  • 9
  • 12
Loading
removed thanks / signature; light editing
Source Link
gung - Reinstate Monica
  • 147.5k
  • 89
  • 406
  • 717
Loading
Source Link
Luciano
  • 649
  • 2
  • 9
  • 12
Loading