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

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Why Use Two Different Tests for Existence of Linear Regression: Value of $R^2$ vs $H_0$: slope $= 0$

I am trying to understand better the tests used to determine the existence of a linear relation between two variables $X$,$Y$. AFAIK, one way of testing the strength of any linear relationship is by ...
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5 views

A model for repeated treatments and repeated outcomes

I have the following data: Measurements of kidney function (in units called GFR) taken at several time points pre-operation (not evenly spaced) and at several time points post-operation. Here's my ...
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14 views

Why does the sum of residuals equal 0 from a graphical perspective?

I've seen the proof for why in least squares regression the sum of residuals is always equal to 0, and I kind of understand why from that algebraic perspective. Basically, you're finding the minimum ...
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11 views

Calculating income elasticity of demand

My model is as follows: $$Y=\beta_0+\beta_1X_1+\beta_2X_2+\beta_3X_3+\beta_4X_4.$$ My income variable is represented by $X_2$. When it comes to calculating the income elasticity of demand (demand ...
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52 views

Can I leave out certain variables that might be accounted for?

I have a dataset that I am trying to use to predict a patient's outcome based on a bunch of factors related to the pateint's care. One of the independent variables is a unique ID number of the ...
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14 views

Error in Pearson correlation, 'y' must be numeric [on hold]

I'm running a regression modelling with GLM between train and validation variables. All the variables are in numeric values. But there is an error when i try to run correlation with an error: 'y' must ...
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15 views

What do my residuals say about my data?

I am new to R and I am trying to find a relationship between Wing length (mm) and Weight (g) of black-capped chickadees using a data set of over 4000 data points. I did a regression analysis and ...
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14 views

Is regression line (for a simple “Y given X” regression, no interaction etc) always unique?

Is it possible for more than one "linear regression" line to fit a given set of points? (i.e.... "least squares" is minimised equally in both cases) I'm assuming a simple one-variable regression in ...
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25 views

Using F-test for (generalised) linear models

I am working with regression on a data set and I am looking for a way to compare the results. From the data ($x$) and observed values ($y$) where $y\in[0, 1]$, I have three models: 1 (baseline): ...
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7 views

sample size for time dependent binomial distribution or logistical regression?

Background I have a membrane of roughly 30000 individual cells that is being flexed back and forth. After some time it fatigues and individual cells start to break. for example after 2000 times being ...
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8 views

Comparing Performance and Determining Scaling

My understanding of statistics is fairly basic, but I'll try to be precise here. Method X of doing something exists and can be timed with a particular method of ...
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5 views

A linear model for testing difference in pairs value between two groups

I have the following experimental design: Values of expression of 3 genes taken from 3 different patients and 3 different controls. R code for generating these data: ...
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10 views

Use of data not captured in a survey for survey glm model

A former statistician in my organization carried out a survey to understand customer satisfaction using stratified sampling. On arriving at the organization, I was interested in seeing how variables ...
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15 views

Difference between pairwise t test and multivariate linear regression results

I got different results when comparing means of different groups using a pairwise t test and multivariate linear regression. ...
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9 views

Scale a coefficient in a regression

Can I multiple a coefficient by 100? For example, Y= b0 + b1Distance Distance is in metres If I increase distance by 1 metre, Y increases by b1. Multiple b1 by 100, my interpretation is: If I ...
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1answer
21 views

Multiple binary logit regressions vs multinomial logit regressions? [duplicate]

Lets assume we have a dependent varible which can take on three values: 1, 2 and 3. Is there any differences in running multiple binary logit regressions(ie. 1 vs 2 and 2 vs 3) or the multinomial ...
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1answer
47 views

Is my understanding of regularized logistic regression correct?

I learned that regularized logistic regression helps prevent the model from over-fitting the data. I understand that the function is still technically a high-order polynomial, but the effect is ...
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13 views

The likelihood of response variables in variational Bayesian probit regression

I read the paper Explaining Variational Approximations (J.T. Ormerod & M.P. Wand) and there is a part where they explain variational probit regression with auxiliary variable since the posterior ...
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16 views

what is a regressional study? Does any such study exist? [on hold]

Am a novice in statistics just want to get schooled from this site on basic statistical matters.
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10 views

How to interpret clmm output

I am using the clmm() function from the R package ordinal. I understand that the ...
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17 views

Confidence interval of linear regression variable calculation [duplicate]

I want to be able to calculate the confidence interval from the estimated coefficient and respective standard errors. I have a linear regression model which can be summarized (in R): ...
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59 views

Any necessary EDA before logistic?

I wanted to know if we do EDA before logistic regression. Sure, I will look at the variables and their distributions, but is there anything specific to logistic?
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21 views

Distribution of the estimate inside the prediction interval while performing linear regression

I would like to clarify how to interpret the prediction interval (PI) that we get while performing linear regression. I realize that PI provides us the uncertainty in our estimate of y when X = x, ...
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27 views

Loess vs Logit Models

How do i compare loess and logit models ? I want to look at the AIC but the AIC function in R does not accept a loess object. Most of the functions available online for loess AIC are calculating AICc ...
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26 views

Probability of a point fitting a line

I am trying to classify between two groups a set of points given two variables (size of the space = L and points of the space occupied = N). At the moment I have a sample size of 620 samples with ...
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6 views

How to interpret the fitted functions in a GAM?

I don't understand how much I can trust in the fitted functions estimated in a generalized additive model. Look for instance to the plot b. The estimated function appears to be increasing but the ...
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20 views

Scale of weights in Gradient descent for Linear Regression

Let's take a very simple example where one wants to get a linear model of weight in kg of people given their height in cm as input. We then have two weights: the bias $w_0$ and $w_1$, and we want a ...
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compare regression coefficients between subgroups [duplicate]

I’m doing a research about differences in effective tax rates between different groups of firms ( SME, domestic large and multinational). I use OLS regression (with robust standard errors). I like to ...
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40 views

How to choose factors in constrained Linear models?

I was trying to do a linear model analysis where the parameters are constrained (sum to 1 and non-negative).But I found that is not obvious how to apply AIC function(or others) to the parameters ...
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31 views

Best linear fit [duplicate]

Which one is the best fit according to these information? fit1 or fit2. I am NOT working with this in an academic context so explanations are not important to me.
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23 views

Regression modelling with mixed data set: categorical and numerical predictor variables

There are thirteen predictor variables which are a combination of 8 continuous, 4 binary and 1 categorical variables. The dependent variable is again categorical. I understand that I need to use dummy ...
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23 views

Predicting Barometric Pressure Based on Wind

I'm working on a script that populates missing Pressure values based on Wind using R's lm(). In the NOAA HURDAT dataset, a large chunk of the pressure values are ...
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2answers
30 views

Why is the probability of my chi square statistic equal to 0

Binary logistic regression in R I have derived the chi square statistic and degrees of freedom for my model (200.7839, 8, respectively) however, when I attempt to determine the probability associated ...
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7 views

how do you calculate nearest neighbor calculation times

I have this question: Suppose you are creating a website to help shoppers pick houses. Every time a user of your website visits the webpage for a specific house, you want to compute a prediction ...
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12 views

Testing difference between two linear regression models

I'm trying to determine which test I use to find if there is a statistically significant difference between two linear regression models in spss. I also need to do a power calculation to determine ...
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6 views

Breusch Pagan test vs graph

I have data where there is one dependent variable (X) and one dependent variable (Y). When I fit a linear model to this and look at residuals vs X, I see that there is heteroscedasticity. Whereas, ...
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56 views

compare two linear models. Linear regression

I have made two linear regressions to estimate y and I get this results: One: ...
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17 views

Transformation of dependent variable for MARS algorithm?

I am just wondering if its necessary to transform a dependent variable as it is a large monetary value? I'm unsure if its necessary with a non-parametric methods such as MARS. When I do a log ...
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9 views

Regression: Finding meaningful counterexamples for a claim about implications of population rank conditions

Situation: In regression settings with stochastic regressor matrix $X$, one needs to impose assumptions on $X$ to validate inference. It is custom to specify these assumptions with respect to the ...
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plz anyone can write commands of this barplot thanks in advance [on hold]

Need comands of this barplot in r packege
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Minimum mean squared error linear combination of random variables

Consider the following objective function: $$ \mathbb{E}((Y-X\beta)^2)\rightarrow \min_\beta $$ where $Y$ and $X$ are (generally not independent) random variables and $\beta$ is a constant. That is, ...
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13 views

power of regression coefficient tests

does anyone know how I can calculate the power of a regression coefficient test in R? for example we have: H0:B0<=9 and H1: B0>9 if actually ...
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1answer
15 views

Binary Logistic Regression with multiple binary and ordinal independent variables

In my data set I have one dependent variable (dead or alive) and 37 predictor variables. 35 of my predictor variables are dichotomous (Obese: 1 or 0, Female 1 or 0, etc), however 2 of my variables are ...
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28 views

Is there a model with additive effects for always positive dependant variable?

When modeling a dependant variable always positive and continuous, models as log-transformed linear model or GLM with log link are generally used. The log-transformed linear model is : ...
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1answer
48 views

How to find “theoretically best” model?

Given the common problem of predicting response variable $Y$ from predictor variables $X$ and $Z$, is there any way to determine the "theoretical best" prediction possible for a response variable? ...
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33 views

Regression discontinuity design

I am trying to apply an RRD design to a set of spatial data from rasters. The approach has been widely used in the development economics literature and I know that it is a sound methodological ...
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19 views

Interpreting factor effect in a logistic regression

Say I'm working with a biological system where two (or more) genotypes are reared under a series of daylength treatments, and scored for a binomial response variable y. I want to know whether the ...
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12 views

Can FTRL be applied on linear least squares? or is it just for logistic regression models?

I'm exploring follow-the-regularized-leader FTRL proximal gradient descent: paper, reference implementation. Everywhere FTRL is mentioned, the loss surface for the gradient decent is the ...
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26 views

Error using lrm function with factor [on hold]

When I try to use the lrm function from the rms package I get the following error when I add a factor Error in X[, ...
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2answers
55 views

Does cross-validation on simple or multiple linear regression make sense?

Does it make sense to apply train-test split or k-fold cross-validation to a simple linear regression model or multiple linear regression model? I'm really confused about this because I saw this ...