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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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Hausman Test Reults Report

I've been working on a research project using a multi-level regression model, and I'm currently figuring out how to present the Hausman test results. I've seen some papers where authors mention doing ...
Sabrina's user avatar
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2 votes
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Tradeoff between Prediction Interval Accuracy & Mean Squared Error

My goal is to quantify the prediction uncertainty in a model regressing climate covariates against GDP. I start with a model with temperature as a third degree polynomial, country fixed effects ($\...
hayfreed's user avatar
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Is there any value in models that have a larger out of sample RMSE than a standard deviation?

I am predicting y values from x values using various regression models, elastic net and partial least squares regression (PLSR). To quantify performance of models we utilize root mean squared error (...
Sir Veza's user avatar
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Recreate `lm` Categorical Regression

Consider the code, which contains regression using lm of two categorical and one continuous variables without interaction using data from the correct model: ...
温泽海's user avatar
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1 answer
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Is differential follow up periods in survival analysis a problem?

I'm looking to compare mortality post-operatively following two different surgical techniques. due to technological advances, one of these surgical techniques was only performed around five years ...
MFA's user avatar
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Gaussian linear model marginal likelihood under g-prior

Consider a Gaussian linear model with an $ n \times 1 $ outcome vector $ y $ and an $ n \times p $ matrix of centered predictors $ X $: $ y = \iota\alpha + X\beta + \varepsilon \quad \quad \varepsilon ...
yrx1702's user avatar
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Does artificially balancing outcomes in regression lead to poor calibration? If so, how to show the poor calibration?

In "classification" problems, it is common for there to be unbalanced-classes. To combat what appears to be a problem (though I would argue that it usually is not a problem), it is common ...
Dave's user avatar
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Can I use a simpler model (small R²) to get more statistically relevant results?

I am new to this kind of stuff. I am currently writing a bachelor thesis that uses data from the European Social Survey (round 7). 4 important questions that I'm using were not answered by every ...
Michael L.'s user avatar
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Poisson two-way ANOVA test for Before and After treatment (including a control)

I am having trouble to determine what type of test to use in this experimental design: My data is like this: I got 10 treatment sites and 4 control sites I got replicates for each treatment and ...
Sergio Nolazco's user avatar
0 votes
1 answer
23 views

Should I Use Regularization in Univariate Logistic Regression for Diagnostic Methods Comparison?

I am comparing two diagnostic methods, Method 1 and Method 2, where Method 2 is considered the gold standard. I am using Method 1 to predict the Method 2 using logistic regression. My dataset contains ...
Daniel Gustavo's user avatar
1 vote
1 answer
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What are some issues with using robust standard errors when you do not need to?

I've been reading the web about this. Some text books mention one line in passing that it can violate some assumptions but never really say which ones. When googling I seem to get into a rabbit hole ...
user2330624's user avatar
5 votes
2 answers
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I think standard deviation of y is related to size of x. How do I create a model for this / test this?

I have a sample of data $(x_i, y_i)$. I hypothesize that $y_i$ is not dependent on $x_i$, but the standard deviation of $y_i$ depends on $x_i$ More concretely, say I assume $\textrm{Var}(y_i | x_i) = ...
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Predict change in dependent variable over three time points using independent variable at baseline

I want to predict the change in my dependent variable (DV) over time using an independent variable (measured only at baseline). My DV was measured at three points in time. The easiest way would be to ...
Johannes Wiesner's user avatar
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10 views

Is covariance estimation via the inverse hessian method generalizable (or possible) for loss functions other than least squares?

I know from other resources such as here that the scaled inverse hessian of your least squares loss can be used to estimate your model's parameter uncertainty (specifcally, covariance), but I can't ...
Will's user avatar
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Non-independent explanatory variable in regression [closed]

I've been getting a refresher course on regression online, no teacher, and in basically every cases aside from Generalized Linear Mixed Model, the independence of explanatory variable is assumed (...
Yo Pomdpin's user avatar
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Why is the threshold term incorporated into the weight vector in linear classifiers?

In the context of linear classifiers, such as the perceptron or logistic regression, I understand that the decision boundary is defined by a linear combination of input features and weights, plus a ...
Narges Ghanbari's user avatar
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Can I use a variable from Principal Component Analysis (PCA) as outcome Y in a linear regression [closed]

(1) I have a set of 3 predictors which predict an outcome Y (BF10 = 10). Each predictor alone does not predict Y (BFincl < 1) (2) I would like to assess if another predictor can predict those 3 ...
KB02's user avatar
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4 votes
2 answers
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Standard negative binomial regression when counts are mainly zeros?

This question must have been asked many times before but I can't find an answer. I'm getting very confused about when to use a zero-inflated negative binomial regression vs standard negative binomial ...
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Bayesian Mediation Analysis

I have: 1 binary outcome (0, 1) 1 continuous quantitative mediator 1 continuous quantitative predictor I would like to compute Bayesian mediation analysis with Liu et al. (2023) method. The formula ...
KB02's user avatar
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1 vote
1 answer
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Optimal sequence analyses and hypothesis testing

I am working with data in R using the TraMineR package. I am fairly new to this type of analysis, so please bear with me. I have a list of unique states (Ex: "NN", "s2s", "...
user17451520's user avatar
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Elasticity from differenced log-level regression

I have the regression $ \Delta \ln Y_i = \alpha + \beta \Delta X_i + \varepsilon_i $ where $\Delta \ln Y_i = \ln Y_{t,i} - \ln Y_{t-1,i}$ and $\Delta X_i = ((X_{t,i} - X_{t-1,i}) / T_{t-1,i} ) \cdot ...
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0 answers
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Does the linear regression fit follow the inverse relationship? [duplicate]

I fitted a X =logA, Y=logB with a weighted linear regression and I got the result as log B =(0.53 $\pm$ 0.054)logA + (17.41 $\pm$ 1.7). When I did the fit with X=logB, Y=logA, I expect the ...
Ashwin Aravindaraj's user avatar
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Are $X_i \varepsilon_i$ iid?

Take: $X_i , \ i = 1, ... , n $ iid. $\varepsilon_i , \ i = 1, ... ,n$ also iid. $X_i \not \perp \varepsilon_j$ (they are not necessarily independent) Are $X_i \varepsilon_i$ iid ?
Lohey123's user avatar
1 vote
1 answer
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My data is clustered in space, how can I account for that in a GAMM?

I am modelling whether a bird nest is build or not based on the date it was built, the geographical coordinates where the nest was built, and using the year when the nest was built as random effect - ...
Teresa's user avatar
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1 vote
1 answer
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Analyses for a vocabulary profiler data

I am writing a paper which uses data from vocabulary profiler (a tool that tokenizes and analyzes a text, output is something like "This text consists of 20% of Level X vocabulary, 20% of Level Y ...
Xun Huxian's user avatar
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0 answers
26 views

Bayesian Logistic Regression: default uninformative priors choice on JASP [closed]

I'm currently trying to perform Bayesian logistic regression using JASP. For this, I need to choose a prior distribution. JASP offers the following options: AIC, BIC, EB-local, g-prior, CCH, Beta-...
KB02's user avatar
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3 votes
1 answer
115 views

Validity of AIC When Comparing Models with Varying Dispersion Parameters

I'm currently making a binomial model with a logit link, which is parameterised as a quasibinomial since I'm allowing it to calculate the dispersion parameter. I was wondering, since changes to the ...
Daniel's user avatar
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0 answers
18 views

Why does the square term get omitted in Gradient derivation of parameter θ-th

I get it that my question may sound a bit sophisticated or overwhelming, but it's pretty straightforward when you read the image below. As you can see, the square ^2 completely dissipates, despite ...
iHunter's user avatar
2 votes
2 answers
53 views

Justifying Residual Histograms and QQ Plots for Linear Regression

Conceptually, I am having a hard time as to why we consider the quantile-quantile plot for linear regression diagonistics, and I cannot seem to get a clear answer after searching extensively. The ...
LateGameLank's user avatar
2 votes
2 answers
36 views

What methods to use in pre and post testing?

I am currently running a pre- and post-intervention study. My hypotheses are if the intervention has an effect and if personality traits moderate the effect of the intervention. I have an initial ...
Maxon's user avatar
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7 votes
2 answers
285 views

How much dispersion is too much for quasipoisson regression?

Quasipoisson regression goes beyond standard poisson regression in taking into account overdispersion (whereby the dependent variable's variance is much greater than its mean). This is explained at ...
rolando2's user avatar
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The function step.lmRob() is not working [closed]

I have a linear model, which i analyzed (in R) through: lmrob_object<-lmrob(diff_mg ~ age + bmi + energy + fiber + ca + phos + iron + potas + supp + uni, data = data), where: diff_mg is the DV (...
Hussain's user avatar
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2 votes
1 answer
56 views

Multilevel Model Residuals Scatterplot Assumptions

I am conducting multilevel modelling (MLM) in SPSS (mixed modeling) to analyze cross-sectional repeated measures data. One of my dependent variables is a survey question scaled 1 to 10, which ...
Mark S.'s user avatar
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-5 votes
0 answers
104 views

URGENT: I am building a Linear regression model. Yesterday my R-squared was 0.792. Today, it had dropped to 0.267. I did not change anything. Urgent [closed]

Thank you for your responses. By way of further information, I am using R-Squared because it is recommended for the project I am doing. Below are the 2 files. The one from yesterday with the 0.792 R-...
Sue's user avatar
  • 1
8 votes
1 answer
633 views

How should I analyse TV episode popularity while accounting for time?

I have a toy dataset which contains TV episodes, the date they were released and how many streams they have received: episode date streams The Shadow Realm 2024-03-08 5987 The Forbidden Tome 2024-...
Jay Bee's user avatar
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0 votes
3 answers
35 views

Compare the proportion of multiple diseases between 2 groups

I'm conducting an analysis on data derived from two groups subjected to different environmental conditions. Here's a brief overview: Group A: 750 individuals exposed to smoke. Group B: 1500 ...
nhaus's user avatar
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1 vote
1 answer
67 views

Which statistical test would you recommend for this experimental design?

I measured the percentage of individuals that crossed an averisve barrier at six different time points for four different genotypes. The barrier is made out of an aversive substance that the control ...
MarsC's user avatar
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0 answers
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Regression with noises in X. Should I use the unbiased estimator or the OLS estimator for forecasting?

I am working with a dataset that includes variables $Y$ and $X$. I assume that $$ Y = \beta X + \epsilon $$ satisfies all the assumptions of OLS. Based on industry knowledge, I know that theoretically ...
The One's user avatar
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0 answers
28 views

Simple OLS Regression Assumptions

Forgive me; I am new to learning statistics. I am trying to understand OLS simple linear regression better and gain an intuition for the associated assumptions. Upon my research, I have identified ...
LateGameLank's user avatar
0 votes
0 answers
10 views

How to perform model comparison based on multinom( ) function of nnet package in R? [duplicate]

My independent variables are gender and sequence, and the dependent variable is intervention (including 3 intervention methods). I established a multinomial logistic regression model to examine the ...
zhang xia's user avatar
2 votes
1 answer
32 views

How to perform model comparison based on multinom( ) function of nnet package in R?

My independent variables are gender and sequence, and the dependent variable is intervention (including 3 intervention methods). I established a multinomial logistic regression model to examine the ...
zhang xia's user avatar
3 votes
1 answer
247 views

A model suffering from omitted variable bias can be said to be unidentified?

If my regression model $$ y_i = \alpha + \beta x_i + \epsilon_i $$ suffers from OVB the error contains one variable which we assume correlated with $$ \epsilon_i = \gamma w_i + u_i $$ my estimate of $\...
Three Diag's user avatar
0 votes
0 answers
25 views

How to choose a feature as an offset in GLM Binary Regression

Is there any statistical test to determine that Feature A should be an offset instead of Feature B and Feature C. From what I understand, if in insurance modelling, usually, offset has a connection ...
actsci stud tries2learn math's user avatar
0 votes
1 answer
35 views

Dealing with categorical variables on cox regression

I am trying to fit a Cox regression model to my time-to event data and have a categorical variable with 5 different levels. If I don't leave one of the levels out, then I will have multicollinearity, ...
smgtkn's user avatar
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0 votes
0 answers
14 views

Effects Contrast Matrix for Interaction with Multiple Grand Means

I want to include an interaction between two factors: area and house_type, in my GAM (MGCV), I hope to make a sum-to-zero ...
statmaj's user avatar
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0 answers
20 views

I am confused about the formula SST = SSE + SSR [duplicate]

I dont know why in this case this formula does not hold.. Can someone explain?
user419436's user avatar
0 votes
0 answers
19 views

Why residual term $\epsilon$ is not included in logistic regression specification? [duplicate]

I have a simple question, which bothers me. In the logistic regression context, the odds are defined as: $$\frac{p(X)}{1-p(X)} = e^{\beta_{0}+\beta_{1}X}.$$ I was wondering, why in the literature the ...
Sane's user avatar
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0 answers
21 views

Multivariate t-test equivalent - control versus intervention

Suppose there were two groups characterised by the same dependent and independent variables. Dependent variable = time to treatment initiation - continuous. Independent variable = point of care test -...
EB3112's user avatar
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1 vote
1 answer
45 views

Regression with dependent observations of only one individual

Last week, I received a task to plan an analysis that my team wishes to perform. My objective is to measure if one physician agrees with the outputs that a certain tool generates for a set of N ...
kKodorna's user avatar
3 votes
1 answer
220 views

Can I include a variable related to the outcome variable into statistical analysis?

My research question is about the contact patterns during the pandemic and what characteristics of people who contacted more person during the national lock down. The outcome variable is a variable ...
Chao's user avatar
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