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The parameters of a regression model. Most commonly, the values by which the independent variables will be multiplied to get the predicted value of the dependent variable.

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Why descriptive statistics contradicts with regression coefficents?

I am estimating a binary logistic regression with L1 norm. According to the regression coefficients, the sign of x1's ...
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3 views

Interpretation and presentation of coefficients for continuous variables in poLCA

I am analysing data on symptoms, signs, and autopsy findings (a set of binary Y/N variables), viral serology, for several viruses, and a few other covariates (Age, gender, site) in pigs. After some ...
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11 views

Cluster points in regression

I am trying to cluster data for a regression problem and wonder if I am way off in my approach or if there is something in it. Problem: make a model of impact of variable L1 and L2 in Output. Output ...
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1answer
38 views

How can a variable have a positive association through logistic regression, yet a negative association through Cox regression?

I am undertaking some medical research using R. My outcome of interest is mortality in the intensive care unit. Data My data looks like this (there are ~15,000 rows). ...
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7 views

Checking for change in significance of regression coefficient after adding covariate

I'm wondering whether there is a way to check whether a coefficient in a linear mixed effects model changed significantly after introducing a new variable. I have two models: ...
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0answers
9 views

Why do some attributes show null outcomes in multiple linear regression [duplicate]

I am trying to analyze this data by linear regression and found experimental outcomes given below: ...
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1answer
41 views

What explains a sudden change in the magnitude of logistic regression coefficients when increasing the sample size

Last week my team and I discovered a strange phenomenon with the coefficients of a logistic regression (LR). As we included more samples from a static dataset, the magnitude of the coefficients of the ...
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1answer
30 views

Interpretation of regression coefficients with different subsets of independent variables

I have a multiple regression problem. Let's say there is a physical system with a true model: $$ y = b_0x_0 + b_1x_1 + b_2x_2 \;\;\;\;\;\;\;\;\;\; (1) $$ Now, imagine I only have access to a ...
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1answer
25 views

How can I look for correlations between variables with large deviations?

I'm researching the correlation between the magnitude (a measure of brightness) and redshift ($z$ - a measure of distance) for a variety of galaxies called quasars. Plotting the magnitude against $log(...
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0answers
11 views

How to quantify SKU growth by removing the effect of price?

I am having Price ($/litre) and volume (litres) sold information at a Brand and also at a SKU level by weeks. I am looking to find out the SKU brand trajectory/growth by removing the effect of price. ...
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1answer
20 views
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4 views

testing the null hypothesis that two coefficients are equivalent (LR)

I'm running a replication study on Livingston's (2005) examination of reputational effect on online auctions. sellers are divided into dummy quartiles based on their feedback scores. I have run a ...
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1answer
164 views

Different regression coefficients in R and Excel

Asking a separate question because whilst this has been answered for polynomial regression the solution doesn't work for me. I'm performing a simple linear regression. Both R and Excel give the same ...
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0answers
8 views

Scaling of Sentiment Scores (SentiStrength) for Panel Regression

I have a dataset of comment texts with 96k observations, each with individual positive and negative Sentiment Scores based on the SentiStrength algorithm. The positive scores are scaled from 1-5, and ...
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1answer
29 views

Relationship between correlations and model coefficients

I have done a machine learning regression task. I am confused by the correlations and regression coefficient. The correlations of the datasets are depicted using seaborn library heatmap: ...
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0answers
10 views

How to interpret regression results when there are categorical independent variables? (statsmodels | python) [duplicate]

I'm using a toy dataset from sklearn and adapted it for a linear regression framework. In this example, I'm constructing a ...
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2answers
329 views

What is the intuition behind getting a slope distribution in linear regression?

If I understand it correctly, linear regression finds one best fitting line for the given data. It can do it either by using calculus and solving for intercept and slope equations or it can solve it ...
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1answer
26 views

The meaning of coefficients in Multiple Linear Regression

So I am learning about linear regression. The coefficient is the slope of the function, which means how much the dependent variable change due to change of the independent variable. So I make an ...
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1answer
21 views

Large coefficients of covariates in Arima

I got some clue here Large coefficients and std. errors Without scaling the dependent variable (online_unit_sale) my output is as below. Flag1 and Flag2 are the covariates and their coefficients are ...
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1answer
15 views

How to display probabilities instead of log-odds in stata

I understand that logistic regression coefficients are to be interpreted as log-odds. i need coefficients to represent probabilities so i can say something like: "the effect of [some dummy variable] ...
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1answer
42 views

Interest rate control variable GARCH

I'm building a GARCH model which looks if analysts' reports affect the volatility of certain stocks. I was wondering if it would be logical to include the interest rate in my GARCH model as a sort of ...
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1answer
24 views

Log-log specified regression coefficients don't agree with level-level specification

I've got a bunch of data on charities and I'm doing a study on the effectiveness of fundraising in the sector. I've got two regressions. The first is $$\text{revenue} = \beta_0 + \beta_1\text{...
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1answer
56 views

How do Lasso coefficients change as lambda approaches infinity [closed]

I have encountered such a problem. I think 2, 3 and 4 pictures are true, but no. Can anyone help?
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0answers
20 views

Linear OLS regression with aggregates and components

A linear OLS regression is specified as Y = a + b*∑(O+R) + c*R + e, i.e. ∑(O+R) is an aggregate and one of the components, R, is added separately. Results for the regression show that both b and c are ...
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1answer
29 views

How to interpret these R regression coefficient results? [closed]

I'm really super new to R and am doing the most basic stuff for a beginner's statistics class. I've been staring at this question for a while and can't work out what I'm meant to do. Here's the ...
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0answers
10 views

Should I report parameter estimates from model with paths constrained to be equal or unconstrained model?

I have conducted a path analysis in AMOS in which I have constrained two paths to be equal to assess whether they are significantly different from one another. The constrained model was not a ...
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0answers
22 views

How to interpret a VAR model without significant coefficients?

I am trying to investigate the relationship between some Google Trends Data and Stock Prices. I performed the augmented ADF Test and KPSS test to make sure that both time series are integrated of the ...
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0answers
24 views

Numeric Functional Regression coefficients

I'm working on some data where I have thousands of curves in the defined as: $P(t)$ that basically represent eluition profiles of some proteins. My aim is to represent each of this $P(t)$ curves ...
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0answers
39 views

In regression, when partitioning SS among predictors, what determines which predictors get the SS that can be attributed to more than one predictor?

In regression analysis, predictors sometimes correlate (and in my field, psychology, they always do; often because they are simply measurements of the same aspects of human psychology). If predictors ...
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1answer
50 views

Attempting to interpret both Beta Regression and transformed DV model results

After reading a good amount of the answered questions on interpreting Beta Regression results (Best explanation here) and reading through the Betareg vignette, I still feel a lack of confidence ...
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2answers
65 views

Why do coefficients in a binary logistic regression model differ according to the number of predictor variables?

I fit a binary logistic regression model with a single categorical variable, for which I received a coefficient. When I added further categorical predictor variables, the coefficient of the original ...
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0answers
36 views
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29 views

What are the errors of the coefficients of a quadratic regression?

I have performed a quadratic regression in order to determine $y = a\cdot x^2 + b \cdot x + c$ by following the steps depicted in the section 'Find by Hand' in http://www.statisticshowto.com/...
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0answers
5 views

Should I calculate RSS using regression of identity line instead of Estimated values?

I have two paired datasets, one of them has linearly increasing ground-truth fat values (let's call it Ftrue) and the other has fat estimation values trying to guess the first ones (call it Fest), ...
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0answers
21 views

How to deal with various sample sizes in the calculation of a predictor variable?

Let's say one of the predictor variables in a regression model is 3-point shooting percentage. However, some of the observations (players) only have one or two attempts while others have several more. ...
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0answers
10 views

How to compare beta coefficients estimated by negative binomial GLM?

I have run two negative binomial regression models on different sets of counts data, and have two beta coefficient estimates and their standard errors for a variable of interest. I would like to use ...
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0answers
22 views

Hypothesis testing - OLS v M-estimation

I am trying to determine if two regression estimates are different. The first is obtained by ordinary least squares (OLS) and the second is obtained by M-estimation. As a minimum example, fits for ...
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0answers
13 views

Interpretation of coefficient of an index whose value lies between 0 and 1

I am running a simple ordinary least squares regression to understand the effect of parental attitude ($PA$) on Math scores of children. $Math Score_{i}= \beta_{0} + PA_{i}\beta_{1} + Controls + \...
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0answers
67 views

Why are the coefficients in a multinomial logistic regression a matrix?

I am conducting an analysis in which I have 3 different groups and a set of 80 continuous variables that I think can discriminate between the 3 groups. I want to: see if indeed I can discriminate the ...
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3answers
64 views

Converting the beta coefficient from matrix to scalar notation in OLS regression

I've found for my econometrics exams that if I forget the scalar notation, I can often save myself by remembering the matrix notation and working backwards. However, the following confused me. Given ...
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1answer
53 views

Interpreting glmnet Lasso coefficients on dummy variables (multiple levels) [duplicate]

I am trying to apply glmnet's lasso to a set of features in which there are multiple categorical variables with multiple levels. My intention is to let lasso reduce ...
4
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1answer
65 views

Standardized and unstandardized variables yield different results for mixed regression model

I have created two mixed regression models, one with raw unstandardized variables and the same model with standardized variables. When I convert the coefficients from the standardized variables I get ...
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2answers
176 views

Regularized parameter overfitting the data (example)

Possible duplicate of (Why) do overfitted models tend to have large coefficients? How does regularization reduce overfitting? In the Coursera's machine learning course by Andrew Ng, I came across ...
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2answers
29 views

Compare models using residuals

Is it statistically correct to compare two models using their residuals? For example, I have two dose-response models, then am comparing their residuals and concluding they are not statistically ...
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1answer
43 views

Multiple regression with a factor variable in R

I'm trying to run a multiple regression on a dataset in R. The structure of the data that I want to use for the regression is as followed (only showing the variables I want to use): ...
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0answers
18 views

Covariance calculations for slope effect size in meta-analysis?

Goal Calculate covariance between effect sizes in a meta-analysis of relative stability, or the b1 slope coefficient of a regression of $$ x_{T_{k_y}}-x_{C_{k_y}} $$ on $$ x_{T_{k_y}}+x_{C_{k_y}} \...
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0answers
26 views

Non significant intercept in linear model [duplicate]

I am a beginner in statistics so I would like some help with literature. I have a linear model $Y= b_0 + b_1 X^2$ Intercept $b_0$ is not significant (sig: 0,09 > 0,05) but $b_1$ is very significant. I ...
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0answers
40 views

Can I compare coefficient values from different models?

I'm modeling conversions with a logistic regression. Each conversion can have up to 3 events (page visit, fill questionnaire, and call). I have 3 domains let's call them A,B, and C. Rather than using ...
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0answers
13 views

Random Effects for a Reference Group in Mixed Effects Models

I want to check my understanding of random effects with regards to the reference group in a regression. Let's say I want to predict earnings for a population on the basis of individual ...
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1answer
25 views

Relationship between coefficient of dispersion and percent of data points above the median?

If I know the coefficient of dispersion and the median of a data set, is it possible for me to then calculate the percent of data points that are above the median? For example, what if the median is ...