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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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Rank deficiency in a linear mixed model

I have a linear mixed model with 4 fixed factors and 1 random factor: V ~ A + B + C + D + (1|E). I want to compare this model with a model with an additional interaction term. When I add an ...
statuser's user avatar
2 votes
2 answers
40 views

Which way to correct for autocorrelation in GAM in timeseries (corARMA/corAR1/corCAR1)?

I was wondering if there are any noteworthy differences in how to correct for $\text{AR}=1$ in a GAM, where time is continuous considering the three different methods here (the data has been collected ...
aim6789's user avatar
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3 votes
1 answer
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Finding which variable is most associated?

I have a set of data relating to a personality construct - (popularity), I have asked participants to give an overall score for personality and then asked them to give scores for other personal ...
MollyJ's user avatar
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Multiple comparison tests when removing the intercept?

I have a set of 13 different dependent variables, all tested against 9 independent variables. Here's a simplified example of the tests I'm running using R syntax: ...
millie0725's user avatar
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Which Analysis to Use for 2 Likert Scale Questionnaire Groups With Multiple Responses

I have a data set that I acquired through running a questionnaire. The questionnaire consisted of participants having to rate 80 different phrases using a 5-point Likert scale; ranging from Strongly ...
Barry's user avatar
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1 vote
2 answers
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PSPP multiple variable linear regression analysis

I'm just starting with linear regression, and I'm having trouble understanding it. It doesn't seem to make any sense to me. Yes, this is school work, but instead of asking for direct answers, I need ...
Juster's user avatar
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1 vote
1 answer
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Strange increasing in $R^2$ when MAE and RMSE worsened for OLS

I am currently working on my thesis, which involves using machine learning to predict non-stationary and seasonal time series. I am encountering some results that I cannot explain. While I cannot go ...
M. Hansen's user avatar
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1 answer
55 views

The error-rate in "The elements of statistical learning"

This picture is from the book "the elements of statistical learning": I am wondering how the test-error rate is calculated based on how the describe the simulation at the start? How do they ...
user394334's user avatar
2 votes
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Reimplementation of MASS::glm.nb with fastglm [closed]

I'm trying to make a simple implementation of MASS::glm.nb via fastglm. The idea is to get the same output but to make the ...
Giovanni Tinervia's user avatar
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22 views

What type of statistical analysis is recommended for examining variations in risk and protective factors across male and female offending groups

I want to understand how risk and protective factors vary across separate male and female offending groups I have classified them into using group-based trajectory modelling (GBTM). Using GBTM, I ...
Ayda's user avatar
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is scaling necessary for logistic regression? [duplicate]

I'm trying to run a logistic regression algorithm from SKlearn in order to identify some particles and when I rescale the data before the training the model is simply incapable of selecting any of my ...
Hector Freire's user avatar
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How to analyze the driver of a flipped sign regression result?

I have a panel dataset uniquely identified by $i$ and $t$. I am interested in the relationship between $x$ and $y$ and I want to an OLS regression with unit fixed effects ($\phi_i$) as follows: $$y_{...
SXS's user avatar
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Event study regression specification: interacting covariates with leads and lags

I want to create an event study regression specification for the following: $$ \ln(y_{ijt}) = \gamma \ln (x_{jt}) + \tau \ln(p_{t}) + \lambda \ln(x_{jt}) * \ln(\mbox{p}_{t}) + \epsilon_{ijt}. $$ I am ...
specfunctor's user avatar
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60 views

Linear regression predicts probability <0 and >0

I am looking at the relationship between the frequency per thousand population of an event (developing a long term illness) and the probability their income will drop. I expect that if this event is ...
user13948's user avatar
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Target variable standardization for lasso regression

I am working with different models for a regression task. The range of my target variable is very small: I noticed a very bad performance of the lasso regression and elastic net model in comparison ...
Limmi's user avatar
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Is the term 'standardised regression coefficient' ambiguous?

The first Google hit says: This highly cited answer says: Partial r is just another way of standardizing the coefficient, along with beta coefficient (standardized regression coefficient)$^1$. So, ...
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How can I derive the bivariate breakdown of a multiple linear regression?

I recently start to learn causal inference from this website. It claims that "efficient of a multivariate regression is the bivariate coefficient of the same regressor after accounting for the ...
dd ss's user avatar
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Bayesian time varying coefficient

While I am writing a thesis on how the cyclicality of fiscal policy evolves over time in certain countries using Bayesian time-varying regression, there are some questions that I would like to ask. I ...
Yohan's user avatar
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How to translate the set of contrasts over model coefficients into definitions of two nested models for Likelihood Ratio testing?

With the data as below: Categorical predictor: "Group" with 2 levels: Group 1 and Group 2 Categorical predictor: "Treatment" with 3 levels: A, B, C Categorical binary response: &...
AshanaShiiii's user avatar
1 vote
0 answers
32 views

How to test specific contrasts about levels of categorical variables through nested models? [closed]

This is not about obtaining any dataset. I HAVE the dataset. This is not about debugging code, this is about EXPLAINING the way to obtain statistical relationship between the nested models (LRT ANOVA) ...
AshanaShiiii's user avatar
1 vote
1 answer
82 views

Understanding the Logistic regression formula

Logistic regression aims at transforming the linear regression formula and fitting the s curve or logistic function to a particular dataset in order to calculate the probability of a categorical ...
Amelia Nicodemus's user avatar
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GLM with canonical link: Why linear regression over the natural parameter?

So I've been wondering why it is "natural" to extend linear models where we assume $Y\sim N(\mu,\Sigma)$ and try to fit $E[Y|X]=X\beta$ to generalized linear models where we assume $Y_i\sim ...
R.V.N.'s user avatar
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23 views

Deriving a "Clean"/Exogeneous Measure from an Independent Variable

Say I have a variable $y$ and a independent variable $\bar{x}$ (where $\bar{x}$ is a cross-sectional mean), I would like to come up with a new variable say $z = f(x)$ to perform a regression: $$y = \...
KaiSqDist's user avatar
  • 103
1 vote
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Measurement of construct confusion

What are the different ways of measuring a construct? I have three items for one construct. The three questions are derived from articles, and they are used commonly as items to measure the variable. ...
Anu's user avatar
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Proof that regression coefficients are identical for averages over treatments data and raw data [duplicate]

The topic is somewhat related to this question. Let's say Experiment with treatments T0, T1, T2 with four repetitions for each and a response $y = (y_{0, 1}, y_{0, 2}, ..., y_{2, 4})$, one ...
fitzberg's user avatar
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1 vote
1 answer
50 views

Several regressions with different dependent variables

I'm working on a project where I want to compare two groups of participants based on several different metrics. Right now, I'm estimating separate regressions with different dependent variables (i.e. ...
John's user avatar
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13 views

Computing shared variances

Suppose I estimate an OLS regression model with 3 correlated explanatory variables. Then I can decompose the explained variances such as in this image: Source: https://www.researchgate.net/...
Felix B.'s user avatar
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Continuous mixture distribution

I am currently working on the derivation of the negative binomial distribution as a result of a continuous mixture of Poisson and Gamma distribution for regression purposes. To obtain the entire ...
Marlon Brando's user avatar
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4 views

What are the conditions to specify the regressors in Heckman 2 step model

I have the issue of interpreting the STATA command Twostep Heckman model, and also adding fixed effects to the model. My analysis is based on a panel dataset and I want to solve for the selection bias ...
Bugz De Silva's user avatar
2 votes
0 answers
29 views

What model is appropriate for measuring the correlation between two proportions?

Explanation: I have a dataset (say n=100 samples) with two data types associated with each sample (genetic and ecological). I'm resampling the dataset such that I take a random draw of n samples (2, 3,...
akoontz11's user avatar
3 votes
1 answer
318 views

The best interpretable regression model currently

I'm seeking recommendations for explainable regression models for tabular data. I'm looking for approaches that offer a balance between complexity and interpretability – something more sophisticated ...
Karen's user avatar
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43 views

How to resolve the residual versus predicted quantile devation (Dharma plot)?

I have been trying to perform beta regression modeling with random effects. I have sex ratio (0.561, 0.765 etc) as the response variable, and climatic variables + years (1970-2021) as predictor ...
Rahul's user avatar
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1 vote
0 answers
12 views

Potential heteroskedasticity in maximum likelihood

I've created a bad loan classifier model using logit regression and maximum likelihood. The actual v expected comparison of the result is shown below. In order to create the chart, we binned the ...
user11209442's user avatar
4 votes
2 answers
218 views

What causes the parameter phi (precision) to be very small in beta regression (by betareg in R)?

I tried to do a beta regression for a variable affected by age and intimacy, but it did not work well. The value of phi (precision) estimated by maximum likelihood method is very small, and when I ...
TomoChang's user avatar
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8 views

determining if odds-ratio for a numerical x variable and binary y label in logistic regression differs between groups (ie. gender or race) [duplicate]

I've seen people ask a similar question, but I'm still not super clear what the best recommendation would be - I am looking at a binary dependent variable, and multiple independent variables (some of ...
mz.'s user avatar
  • 1
2 votes
1 answer
69 views

Confidence interval over point estimate given regression parameters

In Bayesian analysis, the posterior distribution is often sampled when the PDF is not intractable (often). If the samples are of length $n$, then every index in $range(1,n)$ corresponds to a valid ...
jbuddy_13's user avatar
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0 answers
11 views

Struggling with normalization/Standardisation for machine learning dataset [duplicate]

Sorry for what is probably a very obvious/rookie question. I'm currently doing a data science module for my degree and making very slow progress with the work. The case study i'm doing is around HR ...
Alex Ferry's user avatar
3 votes
1 answer
44 views

How to simulate non-standardized artificial data for logistic regression?

I would like to simulate data for a logistic regression with the predictor variables on their original scale. There are, of course, a litany of similar previous questions (e.g., here, here, and here). ...
the-mad-statter's user avatar
1 vote
1 answer
40 views

question about including an independent variable

I'm seeking advice on whether to include the independent variable 'smoking' (Yes/No) in my analysis. The objective is to examine the impact of COVID-19 on female construction workers. The outcome ...
Science11's user avatar
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0 votes
0 answers
29 views

Interpretation of negative coefficients in ordinal regression in spss

I have built an ordinal regression (logit) in the spss for data in the likert scales. I put the independent variables into factors, not covariates. As far as I understand, this should be done with ...
TylerJ's user avatar
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0 votes
1 answer
25 views

Different estimates of conditional mean parameters from OLS vs ARCH

Consider the market model for security $i$: $$ R_{i,t}=\alpha_i + \beta_i R_{m,t} + e_{i,t}. $$ I estimated the parameters with the OLS method. ...
Mattia's user avatar
  • 141
0 votes
0 answers
30 views

Can you store the value of the predicted variable (Y) at each fold and then correlate the predicted values with the actual data?

In particular, imagine to have a set of features (X) that I use to predict a continuos variable (Y). Is it possible to use elastic net, in a cross-validation framework, use it to predict the value of ...
sup_use's user avatar
1 vote
2 answers
204 views

When should I standardize, before or after a regression?

I have a panel dataset and my dependent variable is the logit-transformed share of farm workers on long-term contracts. I am particularly interested in the effects of two variables, pastoral focus in ...
Mikhail's user avatar
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1 vote
1 answer
70 views

Can I utilize Ridge Regression to update coefficients of a Linear Regression model for a new dataset?

I have fitted a Linear Regression Model using one dataset. Now, I have another smaller dataset that I want to refine the model with. Can I use Ridge regression to update the estimated coefficients for ...
Adham Enaya's user avatar
1 vote
0 answers
53 views

Does a significant interaction & effect imply an effect in both groups? [duplicate]

I'm fitting an interaction model for two treatment groups: water and saline. Participants of the study, at different ages $X$, begin the treatment and $Y$ is measured. I fit an interaction model $$Y = ...
John's user avatar
  • 11
2 votes
1 answer
42 views

Confidence intervals around treatment effect in stratified experiment

Suppose you conduct an experiment, where a population is randomized and treatment is given to the treatment group and you are interested in covariates (stratification has been employed) and their ...
jbuddy_13's user avatar
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0 votes
0 answers
23 views

What is the ARMAX model specification of the following economic setting?

I am currently doing a project estimating electricity prices in France, however, my modelling skills are lacking. I have hourly data on spot prices, which are determined per separate hour, one day ...
Zillah's user avatar
  • 31
2 votes
0 answers
32 views

Correct regression to use for longitudinal pest survey between two groups across multiple sites

THE DATA: We have 3 sites with a total of 36 plants growing in them: each site contains 12 plants (6 belonging to spp1 and 6 belonging to spp2). The size and geolocation of each plant is known. Each ...
theforestecologist's user avatar
1 vote
1 answer
53 views

Linear regression on categorical variable, how to interpret the F-statistic?

I am using statsmodels to fit a regression: smf.ols(formula=change ~ C(location))` where change is a continuous variable. I have a lot of locations and some of the ...
benr's user avatar
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Creating a light image generation model for a specific distribution

I am currently working on how a user can introduce bias in a neural network model. To do so, I am creating an image2image model that only works on the training distribution. For example, let's say I ...
Adrien's user avatar
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