Questions tagged [regression]
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
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Is regression on aggregated continuous independent variable adequate?
I´m trying to analyze some cohorts that reported aggregate data (mean, SD, and n) of a physiological parameter for the outcome of interest, which is a nominal variable but fairly lineal with the ...
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Instrumental variables with lags?
I am new to econometrics so I was hoping to get help with something I didn't understand very well. I have the following regression model:
$$G_t=\beta_0+M_{t}+\epsilon_{t} $$
$G_t$ stands for GDP ...
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How do I estimate the standard deviation of the measured variables in linear regression?
Assuming a linear model:
$$
y = \alpha x + \beta
$$
I make n observations of $(x_i,y_i)$.
Each observation is subject to a measure uncertainty that I assume to be normally distributed with mean = 0 ...
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Regression with highly unbalanced explanatory variable
I have a regression problem where one of the explanatory variables is categorical with 2 categories. My issue is that one category has 90% of the observations and 2nd category has only 10% ...
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Help interpreting GLM interaction effect (Poisson with offset)
I've modelled a count variable using a Poisson glm and an offset variable. I'm looking at the effect of sampled year on the number of times people who are 'old' ( > age x) perform a behaviour ...
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Using GAM to investigate the within-subject variation between several periods
my research question is to analyse intra-individual (within-subject) heterogeneity in contact patterns and identify determinants of stable contact behaviour before and during the lockdown. Since the ...
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Adding interaction to regression: main effect AND interaction non-significant
I've used two models on my dataset:
Model 1: clinical score ~ X + Z: both X and Z are significant.
Model 2: clinical score ~ X + Z + X*Z: X is not significant anymore, and neither is the interaction, ...
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R2_test>R2_train from a published paper. How can it be consistently possible?
This image is from a paper where the author has trained and then tested different models on a small dataset (consisting of 117 samples in total). I had the following observation and their questions ...
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GLMM with interaction terms between two circular predictor variables?
I am running a GLMM to see if several weather and nest box covariates influence occupancy (binary linear response). I would like to include two circular predictors (wind direction and box entrance ...
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Loss functions for target values very close to 0 [duplicate]
I am currently building a regression MLP model to predict a target variable between [0,3]. The distribution for target variable is normal for the most part with a slight left skew. My model is ...
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Boosting for regression trees -- Explanation of the algorithm
I am reading Algorithm on Boosting for Regression Trees from the book "An introduction to statistical learning" by James et al. (2013) -- page 322. I am really struggling to understand the ...
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System of linear equations with more equations than solutions
How can I determine the solutions of a system of linear equations with more equations than solutions?
E.g., I have product A, B ...
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Regression with dummy/control variables added leading to insignificant independent variable
I have some revisions to make on my Master's thesis. One was to add dummy and control variables as I am also looking into demographics.
I have 5 independent variables which were previously shown to ...
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Is there a way to calculate LC50 from a continuous dependent variable?
I'm very new to R and also statistics, so the basics are lost on me. In the past I have done some simple experiments with chemicals and calculating the LC50 from binary responses (dead or alive). ...
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Logistic Regression on German Credit data from UC Irvine
I am trying to learn the logistic regression and encountered the German credit data set (https://archive.ics.uci.edu/dataset/144/statlog+german+credit+data). My query is - how to formulate regression ...
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Based on the scatter-plot that i have made to validate my regression model, that could be considered a good model?
I have a gradient-boost regressor model, i'm predicting value of sentences, which often are round numbers (which makes it annoying to validate).
I have created a scatter-plot to validate my model, x-...
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Odds ratio and p-value
Is it possible that in logistic regression model, one variable has high odds ratio and higly significant and other variable which has low odds ratio but is also higly significant.
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Is it a good idea to add as many predictors as possible in a random forest? [duplicate]
In a regression context, specification of the regression equation is rather important. When we add predictors to the regression specification which are not relevant can cause a misspecification issue, ...
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Independence of regression coefficients
Possibly a basic question but am doubting myself.
I have iid samples $(Y_i,X_i,W_i,Z_i)$. I am interested in performing the two following regressions:
$Y = \alpha_0+\alpha_1 X+\alpha_2 Z$
$Z = \beta_0+...
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Where is there is only set of odds ratio in ordinal logistic regression?
I am running an ordinal logit regression with health status(poor, fair, good, very good, excellent) as the outcome. I understand the difference between ordinal and multinomial outcomes, and read many ...
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Why would an AFT scale parameter be negative?
I am fitting an accelerated failure time (AFT) model to survival data, so:
where are the survival times, is a standard normal variable, and is a vector of covariates. Importantly, is the so-...
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Generating White Noise with `rnorm()` vs. `arma.sim()` in R [closed]
I’ve been working on generating white noise for a statistical task and found that the rnorm() function in R is a straightforward way to create it. Here’s a simple ...
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Finding the true "causative" covariate - in joint versus separate modeling
This is regarding some genetic assignment.
Assume we have two random covariates (SNPs) $X1,X2$, and a random response $Y$ (disease). I believe that only one of $X1,X2$ is “causative” for $Y$ ,
but do ...
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Can I perform an ANOVA on the outcomes of regression?
I was told that it's not usual practice to run an ANOVA off of the slopes and intercepts obtained from a regression.
I made "retinotopy" models for each point on the surface of the cortex, ...
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Interpretation of scatter and qqplot to apply regression [closed]
I am new to applying the machine learning models. I have to find a correlation between 1 continuous dependent variable and 27 continuous independent variables.
In the beginning, I was confused about ...
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Power calculation for distinguishing linear regression slopes between two groups
I would like to estimate the sample size required to statistically distinguish the linear relationship between two variables, x and y, between two groups, A and B, and specifically the slopes of the ...
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How to determine or show if two solutions to linear regression are different
Assume that I have a system and that I can measure both the inputs and outputs of and that I can formulate a solution I want in the form of linear regression: $A \vec{x}=\vec{b}$. Further assume that ...
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Power Analysis for Interaction in Linear Mixed Model
I am trying to run a power analysis for an interaction in a linear mixed model to figure out the necessary sample size.
The model has the following structure:
Y ~ C * X + (1|Subject)
Y and X are ...
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Fitting against residuals equivalent to optimizing global linear model?
Suppose you are building linear models to optimize $r^2$ against a target variable $y.$ You have a current model $m$, and you are considering many candidate predictors $x_1, x_2, ..., x_{1000}$ to add ...
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Weighted least squares vs log transform
I'm sure that I'm going to get somebody annoyed by my lack of research on this question, but I'm not good enough at statistics to know where to go to do the research effectively, so please try to bear ...
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What model or method to use for categorical data with repeated measures?
I am trying to analyze my data, it consists of 2 independent categorical variables (4 textures and 4 impact sounds - mixing and matching them gives me 16 different conditions that each person is shown)...
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Change score as predictor
I want to see if a change in an independent variable (T2-T1) predicts another variable at T2. For example, higher increases in cognitive impairment over 1 year for people with dementia predict lower ...
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Coupled Multivariate Regression and AR(1) Process for the Covariates
I am wondering how to fit the following model:
I have a standard multivariate regression, and a set of covariates X. I want to couple my regression equation with an AR(1) process for the dynamics of ...
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Can I use the Estimate of a model directly without considering the p-value?
This is a follow-up question of (About Multivariate Generalized Regression Mixed Models with negative binomial distribution). The research question is to get the intraindividual (within-subject) ...
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Why different results for linear regression in sem() from lavaan and lm()?
thanks for reading this.
I am a student trying to understand more about statistics for social science questions. I am trying to build equivalence in R between the sem() function in {lavvan} and the lm(...
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What happens when there are errors in the predictor variables?
I asked this question yesterday but I can't log into my account anymore: Using a Response Variable as a Predictor Variable in a Future Model?
After thinking about this question (estimate net cost-...
user423739
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Modeling Transitive Preference
I've conducted a preference test twice on 10 subjects, presenting them with three options in all six pairwise combinations (AB, BA, CB, BC, AC, CA).
I need to determine the following: if each subject ...
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What statistical method to use for binary independent variable and continuous dependent variable
I have a dataset that has columns item, week, and units sold. I have another dataset that has columns group, week, and flag.
The weeks for both datasets lie in the same range. Units sold is continuous ...
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Mixed effects models with only categorical data?
This is my first time trying to run any type of mixed effects models. I have a dataset where I was instructed to use some form of mixed effect modeling (lme4 package) to see if functional traits of my ...
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Multivariate analyses using mixed models vs. other approaches
Multivariate analyses (i.e. several dependant variables) can be performed using mixed effects models. In brief, columns representing the dependent variables are stacked on top of one another into a ...
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Between two variables with weak correlations and no significant prediction rate from simple regression, what are the next research steps?
I am working to determine the association between crime rates and economic inequality using income brackets. I have found that some crime rates are weakly, or almost moderately, correlated with rates ...
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logistic regression: categorical predictor with many levels - appropriate group sizes
I'm estimating a logistic regression model with a categorical predictor with 11 groups. I'm wondering whether I can/should exclude some of these groups (D-K, maybe C as well; see below) b/c of small n ...
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Prediction of a time series AR(1) vs AR(1) with exogenous variables vs Random Forest, why is the performance so different?
Extension of the previous question that only compare AR(1) vs. AR(1) with exogenous variables:
I am currently working on forecasting a time series y using three models: an AR(1) model and an AR(1) ...
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Using a Response Variable as a Predictor Variable in a Future Model?
This is a statistical problem I am working on and I would like to request some guidance from the respected community.
Suppose there is a factory that receives food orders.
The food sits in a ...
user423527
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Given a predictor $x$. under what circumstance would you have high $R^2$ but low $\beta$
Assume I have a time series $y$ and a predictor $x$. Let's say they are both centered at zero.
$$R^2 = 1 - \frac{ \sum (y_i - x_i)^2 }{\sum y_i^2}$$
Now I run a new regression $y \sim \beta x$, in an ...
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Rule of Thumb for Mixed Model
Suppose that we have $n$ observations of $(X,Y)$ pair, where $X$ are real (might be vectors), and $Y$ is real. We want to a linear model. One rule of thumb is that the number of learnable parameters ...
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AR(1) model predictions: Are the predictions shifted by one period?
I am estimating AR(1) one step ahead forecasts for the following data using the following code. The AR(1) predictions seem to perform quite well. However, they seem to be shifted by one period in to ...
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How does SYSTEMFIT from R work (from statistical perspective)?
In R, there is a package for estimating systems of equations with OLS, called systemfit. Initially, this package does not seem to add that much of a value, as I can ...
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Multicollinearity when controlling for a variable
I have a few questions about multicollinearity in my data: I'm looking at a certain type of lesion seen on MRI scans; for each patient I know the volume of those lesions and a metric that captures the ...
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Linear regression model building: Do I need to include variables previously proven significant to a model?
for a school project for an introduction course to linear regression we need to analyze three research questions:
Does fertiliser type affect corn yield? (Yield ~ Fertiliser)
Does corn variety affect ...
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