The parameters of a regression model.

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Relationship: Regression Coeffecient and Line Plot Trendline Slope

Why does the slope of my line fit plot not match the coefficient of the same variable in my regression? For one of the variables, the coefficient is positive while the line fit plots trendline is ...
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12 views

How do you read the coefficients in Structural Equation Model for prediction?

I understand that in regression, the beta weight can be used for prediction. For example: Depression =~ 1 + 0.5*Loneliness Suppose that depression and loneliness are measured with Likert Scale from 1 ...
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36 views

Inconstant logistic regression coefficients each time algorithm is run [SOLVED] [closed]

I'm running a logistic regression to find a relationship between falls and drugs taken by someone. What happens is that every time I re-run the algorithm it gives a different result. The table is ...
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13 views

Coefficient in linear regression changes drastically if additional variables are added. Why? [duplicate]

n <- 100 x2 <- 1 : n x1 <- .01 * x2 + runif(n, -.1, .1) y = -x1 + x2 + rnorm(n, sd = .01) summary(lm(y ~ x1))$coef Coefficients (all significant): ...
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Is there a way to do logistic regression model selection of up to 5 variables each from a pool of ~70 variables

I'm trying to determine the best logistic regression model to estimate the probability of 0 in streamflow rates. My response for the glm object is one vector of the sum of all the days the recorded ...
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36 views

interpretation of coefficients from linear regressions with log dependent variable

I have a seemingly trivial yet troublesome question. Let's consider the following model: $$\ln(y_i)=\alpha + \beta D_i + \epsilon_i$$ where $D_i$ is a binary variable that indicates whether ...
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14 views

Taking differences, indexes or levels in regression analysis?

I am new to econometrics and regression analysis and I am trying to make a decision on which path to follow on my regression. I have cross sectional data, and I want to estimate the impact of ...
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39 views

What does the P value in restricted cubic spline plot mean? [duplicate]

What does the P value in the following example mean? ...
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25 views

Seperate regressions approach vs. interaction term approach

I am writing my thesis in finance, and my thesis advisor want me to do a categorical analysis, where I include control variables. He tells me I cannot simply include interaction terms (i.e. category x ...
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31 views

Interpreting Regressions with (growth) rates as dependent variable

I have several regressions and I care about the interpretation of the coefficient(s) (as marginal effects or very small changes). Y is a variable which is a ratio, e.g. a growth rate or a share (not ...
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65 views

R syntax - Multivariate regression with an unknown coefficient or two, for a dummy (engineer)

Something I rather vaguely asked a few months back, saw the tumbleweed roll by (actually hacked some hardware in the time, to get a few answers) before the question was deleted, so I'll try again on a ...
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23 views

There are low variations in the explanatory variables

I am running a regression and find coefficients of my explanatory variables very interesting (they are dummy variables). When I informed that to my lecturer, he told me that there are not much ...
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Which test-statistics do I use if I just want to test one particular regression coefficient

Hello my Question is this. I want to test a model which has the form: $Y_{i,j}= \beta_0+\beta_1 I_{treatment}+ \beta_2j+\beta_3j*I_{treatment},$ (1) where $i$ is the Identifikation Number and $j$ is ...
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11 views

Comparing a regression in two scenarios

I am looking for some answers regarding regression. I am running a regression in scenario 1 and then same construct measured for a scenario 2, the scenario is different but the constructs are the ...
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1answer
30 views

How to deal with linear regression intercepts with high p-values in dichotomic classifier?

I have used a simple multivariable logistic regression (as you would get by default glm() with logit in R) in a problem of dichotomic classifier with approx. 100 predictors, i.e. quite a lot of ...
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32 views

How do I interpret interaction effects in a log-log regression model?

I have the following model: $\log(y)=\beta_0 + \beta_1 x_1 + \beta_2 \log(x_2) + \beta_3 x_1 \log(x_2) $ In interpreting the % change of $y$ that corresponds with a 1% increase in $x_2$ at a ...
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20 views

Backtransform coefficients of a Gamma-log GLMM

I am analysing data from an exclosure experiment, this means for several years, goats were kept outside a fence and inside the fence, plants could grow without being grazed. Outside the fence, grazing ...
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1answer
10 views

Clarification on Prediction with a Regression Model using Centered Variables

As I understand it, for a regression model, centering the variables around their means can be helpful since it makes the intercept term the expected value of $Y_i$ when the predictor variables are set ...
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13 views

Variable contribution in Poisson regression

I am trying to quantify a contribution of X on Y. Imagine I have a time series (per day) of the next variables: Y, X1, X2 Using a scatter plot on visits vs. each variable I have tested that the ...
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42 views

Finding best model for small volume data

I know, this topic was mentioned many time at this forum. However I failed to find any detailed suggestions. I am currently involved in the analysis of medical data. The way I usually did this in ...
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17 views

Comparing Cox models

We want to compare different methods of modelling a continuous covariate (X) in a Cox model. For example, in the first model we use X in its continuous form. In a second model we categorize X into ...
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1answer
27 views

Survival regression variance estimates

I would like help understanding why a survival regression with no censored data-points does not give the same variance estimates as a linear model (see code below). I think it must be something to do ...
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Hierarchical Bayesian Regression with an Indicator Variable, one group has all zeros for the IV Variable

I'm attempting to form a Bayesian Hierarchical Regression Model and one of my regressors is for an indicator variable. My hierarchy structure has separate group-level regressors related across-groups ...
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91 views

Is there something called “mean coding” (like dummy coding & effect coding) in regression models?

When we perform a regression analysis with categorical predictors, we can use (1, 0), called "dummy coding". The coefficients in this case represent the deviation of the groups' means from the mean of ...
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37 views

“True values” of beta regression coefficients

After simulating survival time, status and covariates for a Cox model, I would like to calculate the bias of regression coefficient estimates. But for this, i need the "true values" of beta regression ...
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21 views

bias of an estimator when the variable is categorical

I want to calculate the bias of the coefficient estimate (beta hat) in Cox regression. But for a categorized variable, for example using quantiles we define a variable with 4 categories, then the ...
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Which way of regression modelling is correct among below options, when the predictor is a product term? [duplicate]

I am modeling a response Y against a predictor X, which is a product of two variables X1 and X2. I am interested in the coefficient of X. Mathematically which way of modeling is correct?: Y ~ X Y ~ ...
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13 views

Coefficient with df=0 in log-binomial model

I am using log-binomial modeling in SAS to model the PR of my outcome given exposure directly since the prevalence is >10% so the OR~PR approximation doesn't hold. Most of my models have converged ...
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1answer
46 views

Interpretation of coefficient in log-linear model with share predictor

There are several questions on the interpretation of coefficients in log-linear models such as Interpreting regression coefficients of log(y+1) transformed responses Log linear model interpretation - ...
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37 views

Sampling Distribution (Variance) of Weight Estimates

I am currently facing an issue regarding the sampling distribution of weight estimates. Problem Statement Given an estimate of a $n \times n$ covariance matrix $\hat{\Sigma}$ of $n$ random variables ...
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25 views

Getting the wrong sign [duplicate]

In a regression, when you get negative coefficient which you know should be positive, why it is necessary to include possible omitted variable that is likely to have positive coefficient and ...
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1answer
52 views

What is the correct way to determine which features most contributed to the prediction of a given input vector?

I am using logistic regression for binary classification. I have a big data set (happens to be highly unbalanced: 19 : 1). So I use scikit-learn's ...
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26 views

Promotion analysis with regression, negative coefficients

I used multiple linear regression to model promotion effects on sales on sample retail store, but some coefficients becomes negative. As a business interpretation, should I consider these promotions ...
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26 views

Combining estimates from multiple regressions

I am interested in using quantile regression to fit the following model at different quantiles of a response variable: (1) y = b0 + b1*g1 + b2*g2 + B*Z where b0 is an intercept, g1 and g2 are dummy ...
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24 views

Comparison of coefficients within one regression

I am running a multiple regression model based on panel data that investigates the effect of different types of firm ownership on a certain dependent variable (OLS-estimators). The two independent ...
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How to Test Collinearity Between GROUPS of Predictors?

I had a model (made with VW, log loss) based on a set of base (p=1000's) predictors. It did not predict well. I added set A of predictors (p=~5 predictors), and it improved immensely. I added set B ...
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38 views

Time varying coefficient in cox model

I have a model for survival after an injury that is borderline passing the Schoenfeld test for the proportional hazards assumption (cox.zph() in R). However, ...
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12 views

coefficients in cumulative link models

I used ordinal package to build a cumulative link model: require(ordinal,quietly=TRUE) fm1 <- clm(base ~ . , data = df_reg) summary(fm1) df_reg is a dataset ...
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1answer
30 views

Backtransforming the vertex of a quadratic function

I have created a model for which it was necessary to scale my predictor values by subtracting by the mean and dividing by the standard deviation of the X values. This resulted in variables centered ...
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1answer
32 views

Interpreting multiple polynomial regression coefficients

I read a couple post on interpreting polynomial coefficients here in cross validate however none of them touch on how to interpret multiple polynomial regression coefficients. Perhaps its the same but ...
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2answers
61 views

How does one extract the final equation from glm poisson model?

I have a Poisson model that is performing well. Now we need to put it into Java code and release it to the world. What is the equation that I plug the Poisson coefficients into? Similar to this ...
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39 views

Interpretation regression coefficient percentage points

I have a simple linear regression model, where the independent variable is defined in percentages (%) while the dependent variable is in percentage points (difference between two yoy %-rates). How ...
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29 views

Contingency table model

Calculate the two regression coefficients and hence obtain the two regression lines from the following data I can find the two regression lines by using the equation y=b0 + b1x for ungrouped data. ...
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2answers
42 views

Logistic regression on all data in order to analyze predictors

I have some experience working with classification, and in those instances we always use a training and a test set (and possibly validation sets). However, I'm currently facing a different problem. I ...
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2answers
110 views

modeling prices with the Hedonic regression

I'm using the concept of Hedonic regression in order to model the prices for real estates. I'm having some trouble with my approach. What I have and what I do my data consists out of real estates ...
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28 views

Ranking the performance of countries (entities) from a panel-based fixed effects regression

I am performing a fixed effects regression analysis on countries, $i$, over a time period $t$ with regressor $X$ and outcome $y$ so that the equation is $y = \beta_0 + \beta_1 X_{it} + \epsilon_{it}$ ...
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35 views

regression with constraints on coefficients in R returns bad results

I used the method pcls in order to make a simple regression (price ~ livingArea) with constraints. I set the constraint for ...
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1answer
41 views

Confidence intervals of coefficients of multiple regression

With following model of mpg vs other variables in mtcars dataset: ...
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1answer
30 views

Using standardized coefficients for relative importance with factor predictors

I have following dataset which is modified from birthwt dataset of MASS. ...
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35 views

Regression and ANOVA of factors

I am doing research on automated banking service quality. In my work I have found in total 6 dimensions (factors): 4 service quality (SQ) factors, 1 customer satisfaction (CS) factor and 1 loyalty ...