Questions tagged [regression-strategies]

Regression Modeling Strategies

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1answer
25 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 (...
1
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1answer
36 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 ...
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1answer
56 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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22 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
35 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 ...
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1answer
71 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
123 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 ...
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0answers
29 views

Should stratified cross-validation be used in a regression context?

After a number of Google searches and looking at various stack posts, I cannot find much information or discussion about using stratified cross-validation in regression context. I am modeling forest ...
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3answers
336 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 ...
3
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1answer
66 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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33 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 ...
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1answer
24 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 ...
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0answers
47 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 ...
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2answers
756 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? ...
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1answer
81 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 ...
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1answer
131 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
51 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
34 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
214 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
525 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 ...
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2answers
287 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 ...
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1answer
359 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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39 views

Multiple imputation with composite variables

In my analyses, I often use urinary concentrations as measure of exposure to various compounds. As these are generally spot urines, they are 'adjusted' for dilution using urinary creatinine ...
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0answers
29 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 ...
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1answer
59 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 ...
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2answers
87 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 ...
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1answer
29 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 ...
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1answer
32 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 (...
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1answer
46 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
46 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. ...
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0answers
46 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) ...
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1answer
179 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 ...
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1answer
58 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
108 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
115 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 (...
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3answers
551 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 ...
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1answer
657 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 ...
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1answer
121 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 ...
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1answer
166 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 = ...
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0answers
409 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 ...
18
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2answers
826 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 ...
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1answer
328 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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0answers
20 views

Standardised rates

I'm having trouble understanding the common practice of standardisation in ecological studies involving mortality/incident rates. Based on this paper by Jeffrey Milyo and Jennifer M Mellor advocates ...
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1answer
40 views

How to model environmental factors in a regression - and how does it not introduce multicolinearity in this specific case?

I am reading an analysis which takes a model that regresses a response variable (= criminal activity) on a socio-economic independent variable (= parent salary during childhood). The parameters are ...
0
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1answer
40 views

Is there a acceptable replacement for Poisson regression for this case?

I am very much a novice. I am trying to model a data that contains non-integers and zero values. The data contains the number of prescriptions written per county versus the number of overdose ...
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0answers
147 views

Why is the penalty in the logistic regression likelihood ratio test different from the penalty I specified when fitting the model?

I'm fitting a penalized logistic regression model using the rms package in R. When I print the result, the penalty in the model likelihood ratio test is different from the penalty I used to fit the ...
0
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1answer
118 views

Obtaining the odds ratio of a 2x2 logistic regression interaction in rms

I am using the RMS package and attempted to obtain the adjusted odds ratio for a logistic regression interaction. There does not seem to be a straightforward way to do this. I have decided to obtain ...
0
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1answer
528 views

Reporting the effect of a predictor in a logistic regression fitted with a restricted cubic spline

I have been playing around with using restricted cubic splines using the RMS package. Output below. ...
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0answers
321 views

package 'rms' - singular information matrix encountered

I am trying to fit a binary logistic regression model using only one predictor. After consulting a loess plot I decided to use restricted cubic spline to fit the curve (with default 4 knots). Using '...
0
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1answer
49 views

Seeking regression modeling strategies for predicting prices based on categorical variables (one of which is ordered)

I have a question similar to this one, which never received an answer. Let's say I have widgets that have different quality ratings $q\in\{0,1,\dots,N_q\}$ and which are in different regions $R\in\{...