Questions tagged [regression-strategies]
Regression Modeling Strategies
294
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21
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Autocorrelation of journeys along a route
I have a data set where I have journey based data from buses, and how long time it took to travel a said bus-stop (starting from stop 4). I have multiple such journeys recording, and they are kept in ...
- 229
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39
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Analysis with data from different sources
I have data from 3 different sources, measuring different variables for different samples taken from the same population (a country). All of the data is from country-wide studies and should be ...
- 93
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31
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With what argument can I use splines method in a binary logistic regression analysis?
I want to run a binary logistic regression and I guess some variables have nonlinearities. So I want to use splines method to understand affect of each range in a continuous variable. When I 'guess' ...
- 129
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64
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When fitting a generalised additive model, how to choose how much to smooth?
When fitting a GAM, is there a rule (of thumb) for deciding if $k$ (max number of degrees of freedom for a spline) is large enough or not? How much should edf be below $k'$? And is that an absolute ...
- 189
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2
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86
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Breaking the regression line into two pieces
My X & Y variables are associated like this below and I am trying to fit a simple linear regression model (y ~ x , data= df) , to estimate ...
- 409
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1
answer
23
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pmin(x, 60) and subset regression [closed]
Is there any difference between
y ~ pmin(x, 60) + sex , df = data
and
y ~ x + sex, df = subset(data, x <=60)
If they are ...
- 409
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23
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Is it okay to run multiple regressions for each level of a predictor? [duplicate]
Suppose I want to test the effect of stress on the amount of uttered insults in three groups (psychologists, doctors and lawyers). The most direct thing that I can come up with would be a Poisson ...
3
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1
answer
90
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How damaging to the analysis would it be to run probability validation (`rms::val.prob`) when calibration (`rms::calibrate`) is the correct action?
If I make a model that predicts probabilities (e.g., logistic regression or a neural network), I would like it to have the property that, when it predicts a probability of $p$, the event happens about ...
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69
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How to compare the expected change in a exponential decay function with the expected change in a square root function?
I have two two datasets. Each contains two variables. There is one variable that is present in both datasets.
When I plot each dataset to see the relationship between the two variables in each, I find ...
- 1,218
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2
answers
42
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Change per capita, logarithmic change or non logarithmic change?
I am currently working with Covid-19 key figures such as registered cases of infection and death.
My data is a panel dataset across time and municipalities in Denmark, the set consists of several ...
- 15
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1
answer
783
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Walk through rms::val.prob
The val.prob function in the rms R package has similarities to the ...
- 46.7k
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1
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2k
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Walk through `rms::calibrate` for logistic regression
The calibrate function in the rms R package allows us to compare the probability values ...
- 46.7k
5
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1
answer
125
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Can I interpret coefficients for "Year" as differences between years that are not explained by my predictors?
I am doing statistical analysis of a natural experiment that consists of multiple years of measurements. I have two independent variables that are physically related to ...
- 289
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1
answer
329
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Meaning of interaction with %ia% in rms? Three-way interaction?
In this very illustrative post on evaluating added value of predictors by Frank Harrell, he codes a logistic regression model as such:
...
- 49
3
votes
1
answer
176
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Estimating regression optimism using the bootstrap
I am estimating optimism bias in for example risk predictions. A method for doing that is described by Frank Harrell and implemented in the R package rms. I am ...
- 1,035
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1
answer
50
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Articles about data analysis workflow
I am a non-statistician. I have to write a non-English article about my data analysis workflow for a particular epidemiological regression analysis that I conducted.
The article will cover my workflow ...
- 93
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1
answer
82
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Effect size derived from LME longitudinal model: the statistical findings projected back down onto a group of people
I have been studying the change in a metric X with a linear mixed effect model. I have built this model in a multivariate setting, so I can see how each of my covariates (Time, sex, age) affect X. ...
- 210
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1
answer
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Modelling strategies for analyzing an effect of a predictor through higher hierarchical level
What strategies can be considered when a predictor's direct effect can not be measured directly due to unmeasured confounding? However, data has a hierarchical structure (patients within regions) that ...
- 2,003
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1
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72
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Applying count models with rate responses
How do you apply count models to data which is count in nature, but a rate in reality? In such cases, r can handle this to a certain extent, depending on the model, but what is the correct way to ...
- 209
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680
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Boruta Algorithm for Logistic Regression?
Is it okay to use a Boruta algorithm to select features for a logistic regression?
I read several sources, including the source package as well as this site explaining what Boruta does. My ...
- 41
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0
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351
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Logit Regression and F-test: Can I apply the f statistic when variables are non-normal and the output is binary?
I want to do a univariate analysis on a set of variables to see which predict a binary outcome. I want to discard some of them before performing logistic regression.
I am trying to understand if I can ...
- 164
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2
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1k
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External validation of a published Cox PH model
My aim is to externally validate a risk prediction model published in the medical literature that is based on a Cox regression model. I have a dataset with all the variables from the score. I read ...
- 153
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1
answer
664
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Brier score of calibrated probs is worse than non calibrated probs
The question is related to
probability calibration and Brier score
I have faced with the following issue. I have Random forest binary classifier and then I apply isotonic regression to calibration of ...
- 386
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2
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10k
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Handling missing data in logistic regression
I'm trying to do logistic regression, but I can't seem to get the results I want. I have 6 columns of data (one dependent and 5 independent binary variables) and about 100 rows. The problem with my ...
- 31
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1
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643
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probability calibration and Brier score
Assume that I have a binary classification problem. The outcome from classification I am mostly interested in is the well-calibrated probabilities.
The first way to check this is the calibration plot (...
- 386
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43
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Determine minimum data to start with building model
We have developed a basic Regression framework where we try to build models for over 100 configs(stored in a file).
To run :
...
- 133
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answers
120
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OLR with rms: proportional odds assumption
I am fitting an ordinal logistic regression model with rms package. my data involves a three-level ordered outcome (see ...
- 71
4
votes
1
answer
547
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When LASSO selects only parts of a categorical variable?
I want to use LASSO to construct a model and then run a logistic regression on the variables LASSO selects. However, LASSO selects only parts of some categorical variables that I put into it.
Does ...
- 2,071
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2
answers
303
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Excluding the effect of control variables in the assessment of a logistic regression model
I have a logistic regression model with ten independent variables of which two are included as controls. While their inclusion is necessary for correctly assessing the coefficients of the other ...
- 121
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0
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132
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Using "moderately" correlated variables to select controls for a LASSO regression?
In medicine we often have a disease status as an outcome variable and a lot of independent variables in which we want to see if there is some connection. Traditionally, baseline characteristics such ...
- 2,071
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1
answer
128
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How to validate Generalized Least Square model for longitudinal response
I have a dataset with body weights before and in the follow-up visits after surgery, for a group of patients with obesity. Our goal is to fit a model to predict weight loss throughout the follow-up.
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0
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33
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Combining mean differences in regressors and significant prediction and moderation in multiple regression
I am analyzing a survey about career choices with an eye toward demonstrating sex differences in:
1) the means for factors that might be related to career choice (e.g., differences by sex in ...
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4
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1
answer
892
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Conducting a subgroup analysis with regression modeling
I'm conducting a survival analysis using Cox Proportional Hazards regression to identify prognostic factors for cancer patients. My covariates include information such as age, sex, tumor location etc. ...
- 802
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0
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22
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how to choose the best logit model [duplicate]
I have two logit regression models with different AIC. I'm using R. my first model has significant variables and AIC 192.7436. And my second model has 1 non-significant variables but with smaller AIC ...
- 11
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0
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23
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I have a confusion between using 4 different general linear models and 1 singular ones. I have provided with the codes and outputs
I want to check the effect on mass of crickets, I have a fixed linear effect (AltitudeAge), fixed quadratic effect (AltitudeAge^2), random effects (Nymph IDs, population and the incubators they are ...
1
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1
answer
2k
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Number of Covariates in Cox PH Model and Overfitting
I have a small time to event dataset (N=20) where patients are given one of two drugs (drug) at varying doses (...
- 802
2
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1
answer
264
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Fitting model again after variable selection
This question has been asked quite a bit in other contexts (doing LASSO then OLS on selected variables for example), but I'm unsure about how to proceed for this case.
Suppose I have a set of 50 ...
- 78
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1
answer
2k
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Problems from having too many interactions in a regression?
Excluding the 'dummy variable trap', are the problems from including too many interaction terms in a regression any different from the problems of including too many continuous or binary variables in ...
- 1,218
22
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2
answers
1k
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Does LASSO suffer from the same problems stepwise regression does?
Stepwise algorithmic variable-selection methods tend to select for models which bias more or less every estimate in regression models ($\beta$s and their SEs, p-values, F statistics, etc.), and are ...
- 28.2k
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0
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109
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Kaplan Meier Diagnostic Utility
I'm trying to understand a paper that claims to have identified a gene expression signature that can distinguish primary from metastatic tumors. The authors stratify their data into patients with and ...
- 802
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0
answers
303
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Logistic regression with repeated mesures and unique outcome
I have one independent continuous and time-dependent variable X, repeatedly measured (from 1 to 4 times) in different patients during some period of time.
My dependent variable Y is binary and is ...
- 31
3
votes
1
answer
2k
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Interpretting Cox Regression ANOVA
I'm having difficulty interpreting the results from anova() in the rms package. My confusion arises from what information the <...
- 802
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3
answers
779
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Interaction between dependent and independent variable
I am conducting a multiple linear regression on data from a cross-sectional study, and I suspect that there is an interaction between my dependent variable (a disease risk marker) and one independent ...
- 345
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3
answers
3k
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How to reduce predictors the right way for a logistic regression model
So I have been reading some books (or parts of them) on modeling (F. Harrell's "Regression Modeling Strategies" among others), since my current situation right now is that I need to do a logistic ...
- 1,017
5
votes
1
answer
783
views
How to perform cross validation in semi-supervised learning
Suppose in semi-supervised learning, we have labeled set $X_L$ and unlabeled set $X_U$
Is it ok to validate model performance on labeled data only?
How to do cross-validation in transductive learning,...
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51
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Method for testing interaction in regression analysis
I am running a linear model with 6 explanatory variables (5 in classes, 1 quantitative), and would like to test which interaction(s) are eventually significant.
I think an ascendant stepwise method ...
- 21
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1
answer
26
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Trying to test if an increased rate of use decreases total product
TL-DR:
The higher the rate of production on my expendable unit, the less overall product it seems to produce in its lifetime. I want to know how best to model this or 20 pages I could read which would ...
4
votes
1
answer
211
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Why do we even bother running regression models?
I'm working through regression with Intro to Statistical Learning by Hastie, Witten, James and Tibshirani. They break down regression into stages: data cleaning and processing, model building and ...
- 539
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0
answers
66
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What is the best way to choose interactions between continuous variables for Logistic Regression?
I have a logistic regression model that I am working on for a school project. I have about 55 predictors, all of which are continuous. I am relatively new to the idea of "interactions" between ...
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2
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2k
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What is the problem with $p > n$?
I know that this is the solving system of linear equation problem.
But my question is why it is a problem the number of observation is lower than the number of predictors how can that thing happen?
...
- 147