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Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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Comparison of two test metrics

I'm trying to compare two test metrics (Metric A and Metric B) to determine which one better predicts a delta value, which represents a Euclidean difference. I am unsure how to determining which ...
agf1997's user avatar
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1 vote
1 answer
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GAM: Smooth and factor interaction

I am currently working on a GAM. It includes a smooth-factor interaction. I am trying to decide which function is the one I need. ...
Laura's user avatar
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9 votes
4 answers
495 views

Variable is significant in multiple linear regression but not in t-test of the subgroups

I am getting different p-values for a variable in t-test and its coefficient in multiple linear regression so I am unsure which one to believe. As an example, my hypothetical dataset consists of ...
user416771's user avatar
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31 views

Confusion regarding PCA, FA, and PCR?

I learned here: Is PCA followed by a rotation (such as varimax) still PCA? About the relationship between PCA and FA and how they each provide a perspective for looking at the same thing. However, at ...
Ozz's user avatar
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"Important" data points causing problems with nonlinear regression bootstrapping

I am trying to model radar backscatter of a planetary surface. The power which is scattered back to the instrument depends on the angle at which the it observes the surface. The shape of the resulting ...
ampny's user avatar
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1 vote
1 answer
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What changes in swapping predictor and outcome variables in logistic regression

I have a dataset containing a variable representing the source of isolation of a bacterium, with 2 factors, along with multiple other binary variables indicating whether the bacterium is resistant to ...
user416509's user avatar
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0 answers
14 views

Wanting to create a cut-off point for measurement (Length by width) at which an adverse outcome occurs

I am working on a project investigating dimensions of tears in shoulders and how it affects retear rate after an operation. From the literature, age, and tear size (Dimensions AP [width], ML [length], ...
Atham's user avatar
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1 vote
1 answer
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Time series cross validation for trend + tree model

I have a time series data set with ~3 years of data sampled daily from 2021 to 2024. The data set exhibits a trend, and clear cycles with periods of 1 year and 1 week. My goal is to forecast ~3 ...
anon12345's user avatar
1 vote
1 answer
142 views

Regression spline for time to allow for slope changes

Suppose we have a regression / survival model where we would like to model follow-up time using a regression spline. Follow-up time has two phases (first treatment active, and second treatment ...
user167591's user avatar
5 votes
2 answers
132 views

Do tail bounds on probability translate into bounds on expectations?

Suppose I have a bound of the form: $$P(X \geq t) \leq \exp(-t^2).$$ Can I say anything about the expectation of $X$, $E[X]$? In particular, can I get a bound on $E[X]$? Here's the specific case that ...
snickerdoodles777's user avatar
3 votes
0 answers
24 views

How to identify the most important features that impact an ordinal score?

I have 40 rows of 5 continuous features and 1 ordinal score. What statistical technique is recommended for me to identify which features have the highest impact on the ordinal score? I have looked ...
joran.g's user avatar
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How can i create a linear regression model not having the exact same dataset

i want to create a data regression between two financial indexes, but they don't have a perfect correspondence in the data of observation (for example one has the relevations for 17/6 18/6 19/6 but ...
ConfusedConsultant's user avatar
1 vote
1 answer
43 views

on a linear regression analysis, the determination coefficient is 0.99, but the residuals are not distributed normally. How do I interpret this?

So to preface I'd like to say that this is for homework and I am not very good at statistics. Please explain things to me like I am 5 years old.Also english is not my first language. So the homework ...
Sofia V's user avatar
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5 votes
1 answer
201 views

Clustered standard error - intuitive explanation

I understand that the standard error is standard deviation of the sampling distribution about some parameter, for example the sample mean or a coefficient in a regression model. I also know that when ...
jbuddy_13's user avatar
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1 vote
1 answer
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Hierarchical multiple Regression Analysis - Interaction Effect

I'm currently sitting on a research project and I got an output which is confusing me. The hypothesis to be checked is: Self-Efficacy (Centered_KOMP) is moderating the negative relationship between ...
MadameLibelle's user avatar
4 votes
1 answer
84 views

What if path c’ has a negative coefficient, but X - > Y share a moderate to high Spearman correlation?

I am running a mediation model including the variables $X$, $M$, and $Y$. The Spearman correlation between $X$ and $Y$ is +0.4, while the direct path ...
Philipp's user avatar
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3 votes
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Should I adjust for time for different baseline entry time in an observational study?

Suppose I have a dataset with n waves. I will select samples based on a specific criterion (e.g., wave i with event=0; wave i+1 with event=1). Therefore, each individual's entry time is different. ...
doraemon's user avatar
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2 votes
1 answer
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Multiple Linear Regression/ANOVA Help in Excel

I am working on a linear regression model and keep getting zero as my coefficients and the NUM! error as my p-value. I was told to organize the data this way but was then told by someone else that I ...
Professional_Half's user avatar
3 votes
1 answer
256 views

Intercept significant, but confidence intervals around its standardized β include 0

I ran a HC (‘robust’) regression. The intercept is significant, which is reflected in the confidence intervals around the unstandardized betas. However, the CIs around the standardized β are quite ...
mbp's user avatar
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2 votes
2 answers
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Query about one step in AR-sieve bootstrap

I am trying to understand how an AR-sieve bootstrap works. I am reading this paper: Here are the steps which are to be taken to do a sieve bootstrap:- We are given a sequence $ X_1,..., X_n $. We ...
user2338823's user avatar
0 votes
1 answer
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Measurement invariance across groups and time

I want to run a multi-group longitudinal model. Based on prior invariance testing, I can assume scalar invariance across groups and time. So is it appropriate to have both the same intercepts across ...
JoMo's user avatar
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6 votes
1 answer
223 views

Estimating effects in the presence of a mediator

Suppose that one is interested to compare the effect of biological age versus "cognitive age" on a variety of outcomes. Cognitive age is measured by testing intelligence. The outcomes are a ...
Sam's user avatar
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20 views

Correcting data using model residuals

I am trying to follow a method from a paper to correct my data for technical effects. The method suggests to take the central portion of my data to guard against outliers (which I can do), fit a ...
Alan's user avatar
  • 55
2 votes
1 answer
90 views

Sample Size for Logistic Regression

I'm carrying out multiple logistic regression with three independent categorical variables each with more than two categories per independent variable. I want to use the EPV (events per variable) ...
Laura's user avatar
  • 21
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0 answers
5 views

Testing difference in Difference for observations repeated over time pre- and post intervention, with control and intervention group

I want to assess whether the monthly payment of a bonus to health workers starting in January 2023 has increased the number of monthly supervisions conducted. The country has 26 provinces, out of ...
jaak labeeuw's user avatar
2 votes
0 answers
24 views

First and second moments of OLS slope when Conditional Expectation Function is not linear in covariates

Suppose I have a joint distribution of "outcomes" and "covariates", $(Y,X)$. Define the slope of the population "best" linear predictor of $Y$ given $X$ as $$\beta = \...
stats_model's user avatar
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0 votes
0 answers
33 views

Interpreting coefficients in Log-linear model vs. Poisson regression model

I am trying to understand the difference in interpreting coefficients between log-linear regression and Poisson regression models. To clarify, when I use the term "log-linear regression", I ...
mrhumanzee's user avatar
1 vote
0 answers
17 views

Correlated parameters

If I use a regression model for estimating a time-to-event distribution function with several parameters (such as a Weibull), should I consider that those parameters are correlated when I later ...
Carmen's user avatar
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5 votes
1 answer
189 views

Is the total effect from HIV on stroke equal to the direct effect in the Table 2 fallacy paper by Westreich and Greenland

In the paper The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients by Daniel Westreich and Sander Greenland, the authors present a simple example to illustrate how to ...
Boussens-Dumon Grégoire's user avatar
11 votes
1 answer
180 views

Prediction bands for weighted linear regression

For a linear regression of $x_i, y_i,$ we know that the confidence intervals are: $$\hat{y} \pm t \cdot s \sqrt{ \frac{1}{n} + \frac{(x - \bar{x})^2}{\sum (x_i - \bar{x})^2} }$$ and prediction bands: $...
Basj's user avatar
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How to handle Data Normalization in case that a Logarithmic scale is required?

Let's say we wished to build a Regressor (e.g. a Support Vector Regressor) to predict the price of an asset, within a given time span from now on. However, what if the historical data we have ...
Juan Flautista De Torrepacheco's user avatar
0 votes
0 answers
17 views

Specifying interactions, quadratics and ratios in regression model

I would like to model a linear regression with the dependent continuous variable y and the independent continuous variables x and z: The interaction of x and z is expected to increase y, but y is ...
user13117's user avatar
1 vote
1 answer
37 views

Discrete-time hazard model vs. conditional logistic regression vs. logistic regression

I was wondering what is the difference between these three models (discrete time cox proportional hazard, conditional logistic regression and logistic regression). I would appreciate it, if you could ...
user413503's user avatar
3 votes
2 answers
56 views

Perform a weighted linear regression on $x_i, y_i$ by doing a standard linear regression on $X_i, Y_i$?

Let's say we want to do a weighted linear regression between two series $(x_i)$ and $(y_i)$, with weights $(w_i)$, and get the coefficients from the line $y = mx + p$, and the $r^2$ coefficient. Is ...
Basj's user avatar
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1 vote
0 answers
15 views

Is this non-mathematical interpretation of cause-specific vs subdistribution hazards sensible?

I am interested in estimating the risk of readmissions accounting for the competing risk of death. I would like to explain both types of models to people with a basic understanding of statistics. ...
Emily's user avatar
  • 11
7 votes
1 answer
160 views

General Linear Mixed Model: How do I fix 'Rescale variables? Model is nearly unidentifiable' error on glmer

I'm trying to fit a generalized linear mixed model (GLMM), but I'm getting a persistent error. I'm looking at the relationship between weather (continuous variables: rainfall, maxtemp, and mintemp) ...
Hazel's user avatar
  • 71
0 votes
0 answers
21 views

Which is the correct regression model for predicting the association of climate with Julian days nested within decades?

Below is a reproducible example: ...
Rahul's user avatar
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0 votes
0 answers
28 views

Am I using the right method to model my zero-inflated data?

I have a dataset of workplace permits, sample size n=3000. The data is collected between 2012-2020, so if a permit was active some time between 2012-2020, I included it in my analyses. My exposure of ...
user9410's user avatar
0 votes
0 answers
27 views

Is the mean of the Bayesian regression posterior a probability distribution itself?

I know that to find the mean and covariance matrix of the posterior distribution of the regression coefficients, we have to equate the exponents of the product of the likelihood and the prior and the ...
CapBul's user avatar
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3 votes
1 answer
38 views

How do you interpret estimates when the model is the same for two exposure variables?

I want to investigate the direct effect of two environmental variables $X_1$ and $X_2$ on a quantity $Y$. $X_1$ and $X_2$ are connected together and with two other environmental variables $X_3$ and $...
Boussens-Dumon Grégoire's user avatar
2 votes
0 answers
47 views

Comparing slopes of regression models on different data

Let's say, we have two dependent variables: $y_1$ and $y_2$, and these dependent variables depend on their own exogenous regressors: $$y_1 = \beta_0 + \beta_1 x_1 + \epsilon_1$$ $$y_2 = \gamma_0 + \...
Athaeneus's user avatar
  • 205
0 votes
0 answers
17 views

derivative of Logistic Regression with sigmoid func [duplicate]

I am having difficulty figuring out, why I get different answer from the professor. we are tasked with finding the deriative of the logistic regression cost function with the sigmoid function: $$L(w│D)...
Ofek nourian's user avatar
1 vote
0 answers
29 views

Unacceptable results for adj R2

I have a dataset with 19 features. When I ran it with the Lasso algorithm. R2 for test and train was 0.69. But the value of adj r2 for test is 1.28 (above 1), and for train the value is 0.28. What is ...
Erfan Mollai's user avatar
2 votes
0 answers
49 views

derivative of Logistic Regression (sigmoid) [closed]

I am having difficulty figuring out, why I get different answer from the professor. we are tasked with finding the deriative of the logistic regression cost function with the sigmoid function: $$ L(w│...
Ofek nourian's user avatar
0 votes
0 answers
34 views

Propensity Score vs Propensity Score Matching?

I am trying to self-learn about Double Robust Estimation. It seems to me that Double Robust Estimation uses Propensity Scores, but does not use Propensity Score Matching. Here is my understanding of ...
user avatar
6 votes
2 answers
262 views

Count predictor and binary outcome

Is a binary logistic regression the best approach when I have a count predictor and a binary outcome? Can I apply a multiple binary logistic regression model if I have more than 1 predictor that is a ...
stephan_phd's user avatar
2 votes
0 answers
32 views

Assessing heteroscedasticity in residuals vs. fitted values graph [duplicate]

I am running a mixed model regression with 3 levels (schools, groups and students). I applied robust standard errors with the R function ...
Elena García's user avatar
5 votes
1 answer
82 views

Regression Modelling using lme4 in R

I have GPS collar data on a species of desert gazelle throughout different seasons and want to model the effect of seasonal changes in weather patterns on their movement patterns (e.g. daily distance ...
rhyncogale's user avatar
1 vote
1 answer
46 views

Can you use a percentage as the dependent variable in general additive models?

This is more a general question about statistical modeling rather than a project specific question. Can the dependent variable be a percentage in a generalized additive model (GAM)? Is there a ...
DaniH's user avatar
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1 vote
0 answers
57 views

Least-bad stepwise procedure for a simulation that shows issues with stepwise regression

I am well-aware of the issues that stepwise regression causes. I want to demonstrate some of them via simulation in a particular situation. I am thinking of a regression where I have some categorical ...
Dave's user avatar
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