This tag is ambiguous and should be avoided.

146 questions
Filter by
Sorted by
Tagged with
18 views

### Linear Regression using aggregate variable create multicollinearity or adjustment issue?

my group project has a number of independent binary variables x1,x2,...,xm and a dependent binary variable y. My dataset contains some million of rows. Since there are so many independent variables, ...
51 views

### Adjusting for confounding in linear regression model

I am wondering how would the slope and intercept change after adjusting for a confounder factor. After adjustment, would the slope be lower, or higher, and the value for the intercept? Is there any ...
• 21
14 views

### The meaning of "ICC corrected by age and comorbidity is best described in detail"

I received feedback on a manuscript comparing the mortality of two populations. Both crude and adjusted mortality rates are compared. Adjusting was done for age and comorbidity score and it is clearly ...
• 1,513
107 views

### Calculate covariate-adjusted means and 95%CIs for treatment and control group separately for simple 2-arm trial

I have data for a simple 2-arm RCT, that looks as follows: ...
• 103
1 vote
94 views

### Adjust for covariates in small sample size (IPTW, PS match, etc.)

I have a dataset of patients with a grouping variable (groups A (control) and group B (treatment)). The two groups have sample sizes of 170 vs. 30. I would like to compare outcomes between the two ...
• 139
58 views

### Which p-values do I use for FDR in 3 separate multiple linear regression models?

I'm trying to carry out Multiple Hypothesis Testing Correction using adjusted p-values (FDR Method) from my multiple linear regression models. I am testing 11 independent variables of interests ...
1 vote
14 views

### Can you adjust for covariates that have minimal variability/sparse categories?

I'm trying to run a regression on the effect of HIV on sleep and I want to adjust for smoking (one of several covariates). So the model looks like: ...
• 449
33 views

### Adjusted between-group comparisons : single vs separate linear regression approach

Suppose I have 3 groups - namely, "3" , "4", and "5" - and I am interested in comparing group "3" with "4" and with "5" on a continuous ...
• 63
1 vote
88 views

### Including pre-treatment covariates in difference-in-differences: what if my covariates determine treatment but are outcomes of treatment?

I have the following question: What should I do with covariates that affect treatment in the pre-treatment period but are affected by treatment once the treatment is in place in a difference-in-...
34 views

### How to adjust weight data for gender and batch

I have weights from mice raised in 10 batches. I want to adjust the weights for the gender and batch of the mice, so that I can select the heaviest and lightest for further testing. I know I can do ...
10 views

### Age-adjusted mortality rate given age distribution and total number of deaths

I am a bit confused as to how I can calculate age adjusted mortality rate given the two datasets that I have. My first dataset consists of covid deaths per city district and is a gross sum (...
199 views

### How can I deal with a covariate being defined only for a subset of my sample?

My model looks like: ROI_size ~ diagnosis + medication_dose + sex + age. Specifically, I want to find the effect of disease (1 or 0), adjusted for current medication dose (measured in mg) on brain ...
402 views

### Does machine learning methods adjust confounding effect of the variables?

I have implemented machine learning (RF) for analysis of a dataset, evaluating observations' survival. After analysis (including variable importance) one of my collegues asked me that does ML method ...
• 197
460 views

### DAG: interpretation difference of TOTAL and DIRECT effect in terms of adjusting

Could one explain in simple words how examining the total and direct effect differ in terms of adjusting? How to interpret the findings of these two approaches? DAG Minimal sufficient adjustment sets ...
• 1,513
686 views

• 3,785
1 vote
106 views

### Using binary outcome variables in real-world data studies must be wrong?

Please be gentle if it's a stupid(ly easy) question: In medical literature lot's of randomised clinical trials use binary outcome variables, such as 90% reduction in Y, or Y<(a certain threshold). ...
22 views

### Known Correlation between predictors

I have two predictors and an outcome, let's call them x, y and z. I know that x and y are correlated with correlation r. I am trying to construct a linear model: z = ax + by + c I have an ...
27 views

### Highly significant t-test statistics, any way to correct this?

I have been performing several paired t-test, where I test whether the sample means are different between two groups. For all of my tests (approx. 30), which all carries 13-14,000 observations, I ...
• 219
979 views

### Should all adjustments be random effects in a mixed linear effect?

I've been sometimes taught that when you are performing a mixed model, any variable of which you don't care about estimating a parameter (adjusment variable) should be a random effect, regardless of ...
• 1,119
1 vote
731 views

### Significance of correlation with range restriction in x

Background Range restriction can happen in various study designs and it affects the results of bivariate correlation or in multiple regression, for example. In some cases the range restriction may be ...