Questions tagged [regression-strategies]

Regression Modeling Strategies

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0answers
22 views

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 : ...
3
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0answers
67 views

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 ...
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2answers
125 views

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 ...
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1answer
27 views

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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0answers
32 views

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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0answers
148 views

Interpretation of a quadratic term on a log transformed target variable

I've done some searching and found several posts related to this, e.g.: In linear regression, when is it appropriate to use the log of an independent variable instead of the actual values? Suppose I ...
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1answer
134 views

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. ...
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0answers
12 views

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 ...
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0answers
19 views

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 ...
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1answer
347 views

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 (...
2
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1answer
54 views

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 ...
4
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1answer
325 views

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 ...
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2answers
497 views

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 ...
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0answers
60 views

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 ...
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0answers
43 views

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 ...
1
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1answer
449 views

Interpretting Cox Regression ANOVA

I'm having difficulty interpreting the results from anova() in the rms package. My confusion arises from what information the <...
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3answers
229 views

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 ...
9
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3answers
700 views

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 ...
4
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1answer
211 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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0answers
39 views

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 ...
0
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1answer
25 views

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 ...
2
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0answers
59 views

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 ...
7
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2answers
854 views

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? ...
1
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1answer
147 views

recommended approach for building an ANOVA model

Despite reading several online references, including the full Wikipedia article on "ANOVA", I'm still confused at the recommended process taken to build the most statistically significant linear or ...
3
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1answer
366 views

Bias corrected calibration curve (regression modelling strategies)

I have a question regarding calibration plot for a binary logistic regression model (calibrate) in the rms(regression modelling strategies) package. The Bias-corrected curve (see below) shows if the ...
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0answers
66 views

Is Wald statistic sufficient to show no association?

When reporting the results of multivariable regression analyses, I would normally provide either $\beta$ with 95% confidence interval, or the estimated effect size (e.g. between Q1 and Q3). However, ...
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0answers
54 views

how can I obtain a beta value for three way interaction term in a logistic regression

I am using the RMS package in R to conduct a logistic regression that contains a three-way interaction. As part of my modelling approach, I have conducted chunk tests of the interaction (using Wald ...
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0answers
416 views

How to apply a model built using Multiple Imputation to predict on dataset with missing data?

I understand that Professor Harrell recommends using the target variable in Multiple Imputation. An example using aregImpute of the rms package is in his lecture notes: http://hbiostat.org/doc/rms....
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1answer
845 views

Does Regularized Logistic Regression Produce Calibrated Results?

It has been asked and addressed here that logistic regression modelling is calibrated already and there is no need for calibration of it. To me it seems the argument provided there does not follow ...
3
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2answers
635 views

Cox PH model: managing continuous variables and linearity assumption

In an epidemiological study, I'm using martingale plot to assess the linearity of continuous variables. Here are the Martingale Residuals (from Null Model) using R's ...
2
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1answer
826 views

Predictive Mean Matching as Single Imputation?

Multiple imputation is known to be advantageous compared to single imputation. However, in practice there are often non-statistical reasons why multiple imputation can not be used (e.g. the data ...
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0answers
30 views

Correlation Regression

I need some help to figure which statistical analysis will be useful for me. I have 15 variables and one dependent variable "Rate". I need to find out which of the variables have more impact on rate ...
0
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1answer
113 views

Variable with predictor name in Predict.rms

I would like to build regression models for a number of different exposure variables and show the results using ggplot.Predict of the ...
0
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2answers
188 views

Wrong predictions with imbalanced binary data

I have a sample of 3000 observations. I want to study the impact of covariates on a binary dependent variable (i.e. two categories: "yes" or "no") using either a logistic regression or a linear ...
0
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1answer
33 views

linear model using significant outcomes of linear model

I am getting confused about a couple of techniques that I'd like to discuss: I am using an R package that in turn depends on the limma package. I tried reading the docs, but I can't grasp what is ...
0
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1answer
84 views

How to set up a regression for Adjusted Plus Minus with no offense and defense?

So here is the backstory: This is a game with two teams The outcome of the game is that one of the teams wins and the other loses There is no offense and defense We can use tug of war as an analogy (...
0
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1answer
52 views

How to decide the size of the subset of the most relevant features while performing feature selection?

I have a dataset with 25 features(columns). I'm trying to apply forward feature selection to my dataset, which will return a subset containing the best features. But the size of this subset, i.e. the ...
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0answers
51 views

Including many interaction terms in a logistic regression

I have a logistic regression model that is currently of the form: Event ~ Vacc + Age I want to start including interaction terms for different types of vaccine. ...
1
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0answers
47 views

Interpretation of spline models: plot vs estimate

I have conducted regression analyses (cph - using rms package) to investigate associations between an exposure (air pollutant) ...
0
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1answer
289 views

machine-learning : Why training set and test set need to be independent and identically distributed?

My machine-learning book that I'm reading only says that they need to be but not why? My intuition says that if they are that leads to a better learning, if they were not it would be like we are ...
0
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1answer
76 views

Quantiles in ols/cph

I need to conduct regression analyses with continuous and categorised data (as the latter is common in my field). So far, I used to do this as follows: ...
3
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3answers
281 views

How can I find the correlation between groups of *attributes*?

Assume I have data where multiple attributes are measured for countries and the attributes can be divided into dimensions. For example one dimension can be 'Education' and have 5 attributes associated ...
2
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1answer
208 views

For LASSO, what is the best alternative when a held out test set is not viable?

I have a very limited data set with a number of features $\textbf{x}$ (roughly 30 dimensions) and a regression target $y$. I have roughly $20$ groups of data-points with $2$ points in each group (...
2
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4answers
721 views

What is the precise definition of unsupervised learning?

Let's look at a special case: Generative Adversarial Networks (GANs). (For those who don't know what a GAN is: for this purpose they are two neural networks that are trained using user generated ...
9
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1answer
1k views

How to estimate a calibration curve with bootstrap (R)

Question: I have fitted a probabilistic model (bayesian network) for modeling a binary outcome variable. I would like to create a high-resolution calibration plot (e.g. spline) corrected for ...
0
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1answer
213 views

Internal & External validation of ordinal outcome

For binary outcomes, I have used bootstrapping approach (Frank Harrell's R package rms) for internal validation and Cox framework for external validation. More ...
5
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1answer
218 views

Determine rate of change in dissimilarity (distance)?

I have repeated measures plant abundance data for 36 forest plots, across 80 years involving 50+ species of trees. The data are structured as: Columns = ...
2
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0answers
712 views

Confusing aspect of Harrell's bootstrap-based optimism-correction Internal Validation procedure

This bootstrap-based internal validation procedure is implemented in the validate function in Harrell's rms package. It allows ...
23
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2answers
1k views

Bayesian thinking about overfitting

I've devoted much time to development of methods and software for validating predictive models in the traditional frequentist statistical domain. In putting more Bayesian ideas into practice and ...
0
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1answer
654 views

How to plot the calibration curve for an ordinal logistic regression model applied to a test sample?

I'm doing a validation study of an ordinal logistic regression model that was made with the lrm function of the rms package in R. How can I plot the calibration curve for the model when applied to new ...

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