All Questions
25
questions
1
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0
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18
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Rescale measures of association for meta-analysis (e.g., log-transformed independent variables)
I am carrying out a meta-analysis of studies evaluating the association between blood levels of specific environmental pollutants and health outcomes (binary).
Some studies reported OR/RR/HR for ...
- 11
5
votes
1
answer
392
views
Can glm(m) model estimates be negative after back transforming?
I have made three generalized linear models, one with zero-inflated Poisson, the second with negative binomial, and the third with binomial conditional distributions. I am now trying to interpret the ...
- 77
0
votes
0
answers
51
views
Statistical comparison of two (log) probabilities
Using R, I built 2 logistic regression models (with outcome variable being depression status - present or absent) and used leave one out cross validation to obtain predicted values for the dataset. I ...
- 363
1
vote
0
answers
62
views
Calculate difference in log odds between two logistic regression models
I would like to calculate the difference in log-odds between the error of two logistic regression models, given the correct answer aka ground truth (depression present${}= 1;$ depression absent${} = 0$...
- 363
1
vote
0
answers
214
views
What to do with 100% datapoints when conducting a Logit transformation
I have a panel dataset of 120 different countries measuring a variable over three periods. This variable indicates the percentage of 1000 respondents in each country that answered yes to the question. ...
- 11
0
votes
0
answers
32
views
How to add a correction to the parameters in logistic regression s.t. the decision boundary is corrected?
Sometimes we would like to correct the decision boundary of a pretrained logistic regression model $p(y_{temp}=1|x)$, for example by multiplying by a prior in pursuit of adapting better to the ...
14
votes
1
answer
938
views
Why the does the intercept of my null model not equal the mean when I log transform the outcome variable? How do I interpret it?
I have an outcome variable that is right skewed, so I log transformed it. I made a null model with only the log-transformed outcome variable, but when I exponentiate the estimate, it does not equal ...
- 253
1
vote
0
answers
309
views
Confidence interval for a log-log equation
I have the following equation: $\mathrm{ln}(y) = \beta_1 + \beta_2 \mathrm{ln}(x)$.
Assume I have an estimate of $\beta_2$ and its standard error. How do I calculate the confidence interval?
Is it ...
- 11
0
votes
0
answers
2k
views
Interpretation of Log-Transformed Predictors in Logistic Regression [duplicate]
Suppose we have an explanatory variable – GDP per capita – of which we take the natural log.
Suppose further that our dependent variable is the occurrence of civil war.
Running a logistic regression, ...
- 23
0
votes
2
answers
1k
views
How to back transform ln + 1 or log10 + 1, and interpret that result?
I have some issues with my linear difference-in-difference analyses. My outcome is health care costs, where a lot of people have 0 costs and some have really high costs. Therefore, I logtransformed my ...
- 11
0
votes
1
answer
392
views
Fitting a logarithmic trendline on already logged values
This is the situation. I am running trials with a population simulator, which produces various outputs (y), with the variance of these outputs being dependent on the number of clones (x) (recursions) ...
- 3
5
votes
1
answer
450
views
Interpreting GLM with logged variable
For my logistic regression model I have:
glm(reconv ~ -1 + log(precon) + log(age), data = crime, family=binomial)
With the following co-efficients outputted from ...
- 509
3
votes
1
answer
211
views
How can I interpret natural logarithm transformed value in the binary regression result
I have the binominal regression output result using R programming and x3 below is the natural logarithm of the data which is large. The x3 before imposing the natural logarithm has the following ...
- 506
0
votes
0
answers
3k
views
Price elasticity in logistic regression with log price
I'm estimating demand and calculating price elasticity using logistic regression.
In logistic regression with level price, elasticity is
$$ \alpha*price*(1-share)$$
while if one uses log of price, ...
- 123
1
vote
1
answer
2k
views
Log transformation results in a negative coefficient
I am running a logistic regression with 7 independent variables. One of these variables is income. If I don't log-transform income and run the regression, it results in a positive coefficient, however,...
- 11