The parameters of a regression model.

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Insignificant slope coefficients

While calculating the value of the dependent variable why do we take into account even the variable whose slope coefficients were not significantly different than zero? Is my understanding correct ...
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13 views

Why would standardized betas be high (e.g. .66) but non-significant in moderated regression?

Running a moderated regression using PROCESS macro in SPSS (issue replicated by running the same moderation using mean-centered variables in SPSS linear regression command box), I am finding that the ...
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30 views

How to interpret two observations that are otherwise identical in a regression model

I am confused trying to interpret how two observations are otherwise identical but differ by a dummy variable. For example if we have the following model with a factor variable race being White race ...
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1answer
22 views

How to deal with missing coefficients while bootstrapping regressions

I'm using R boot() function to perform regression bootstrapping. When boot() resamples my data, can happen that some coefficients are missing, especially in the case of factor variables with many ...
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2answers
29 views

Evaluating a factor variable

I am seeking feedback on the theoretical appropriateness of two approaches I am planning to follow. I have a dependent continuous variable (y) and several independent variables some of which are ...
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1answer
20 views

Groupwise contribution to regression coefficient?

My intution tells me that the following is a straight forward question, but I could not find relevant answers when I searched for it. I assume the reason for that is that I don't know the relevant ...
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11 views

Overlap between 1) regression results and 2) correlation between residualized versions of variables

Scenario: 1) Regress a standardized variable A ("stand. A") on a standardized Variable B "(stand. B"). Since both Variable A and Variable B have a number of potentially confounding influences on ...
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1answer
48 views

Significance of individual coefficients vs Significance of both

This was a question I read from google quantitative analyst interview on glassdoor: If each of the two coefficient estimates in a regression model is statistically significant, do you expect the test ...
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13 views

Modelling interactions with only a subset of the levels of a factor in R [migrated]

Let's first look at lm. I have a continuous explanatory $X$ and a factor $F$ modelling seasonal aspects (in the example 8 levels). Let $\beta$ denote the slope ...
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18 views

I did ridge regression and i am confused with coefficients

ridd=lm.ridge(mariner~o1+o2+o3,q,lambda=0.001) ridd o1 o2 o3 34.7597607381 0.0001989008 0.0393011905 ...
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28 views

Interpretation and meaningfulness of regression coefficients

I have performed logistic regression on banking data which is trying to predict the bad customers correctly due to the cost involved. I have build a model and pasting a picture of the output obtained ...
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1answer
50 views

interpreting coefficient values in lasso regression

I am running a lasso regression function. I have about 45 features and I am predicting 1 dependent variable. After running lasso regression I get the coefficient values of the features. 1.If I look ...
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1answer
38 views

Why does the amplitude, bandwidth and position of Gaussian change when data changes from positive to negative

I'm trying to fit a single Gaussian to some values in Matlab. When the values are positive, the model fits without any issues. However, when these values become negative, the r squared value changes, ...
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10 views

How to test that two covariates have the same impact on dependent variable?

Given the model $y =\beta_0 + \beta_1 x_1 + \beta_2 x_2 + u $ where $x_1$ and $x_2$ have completely different scales and units, is it possible to test whether their impact on $y$ is the same? i.e. ...
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1answer
47 views

High R-squared although many insignificant coefficients

I just did a regression based on the gravity model where I try to identify the most important factors that determine the trade flows. In total I have 18 variables and 363 observations. In fact I would ...
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1answer
17 views

Quantitative and categorial predictor in one model

This is what I would like to know, due to some logical problem behind! I have a model as: Crown radius = Diameter at breast height + Location DBH is quantitative, like 30cm, 40cm... Location is ...
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27 views

Inconsistent Performance of PCA Results from SPSS

I've completed PCA with my dataset (16 variables) and extracted 3 factors. I then created an Excel spreadsheet where I can enter in user provided data and calculate the scores for each of the three ...
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1answer
37 views

How to check for confounding factors

I have been doing an analysis using a difference in difference setup. In my raw sample I use OLS and first difference (two time-periods) and I get the effect that I would expect. Namely that shocks in ...
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23 views

Is the constant value ignorable?

I am running a linear regression on SPSS. Basically I have 2 independent and 1 dependent variables; and I would like to understand which of my independent variable is more effective on the dependent ...
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16 views

Unit weighting for linear composites / regression

Cohen (1990) mentions a regression that I have not heard about before. Here is how I understand his description: Standardize the dependent and the independent variables Regress the standardized ...
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1answer
56 views

Large value of exp (B) in binary logistic regression SPSS what is wrong? [duplicate]

I had a very large value for Exp(B) in SPSS binary logistic regression. What is wrong and what should I do?
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1answer
27 views

Equation of a fitted smooth spline and its analytical derivative

I need to fit a spline function to a data set. I tried with bs, ns and smooth.spline. In my ...
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1answer
23 views

Beta coefficient interpretion with categorical and continuous predictors in a linear regression

I am trying to run a linear regression with both categorical and continuous predictors. I have coded the categorical predictor (with three levels) into three dummy variables, and entered the two dummy ...
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10 views

Covariance of the regression coefficient of two regression given the correlation between the independent variables

Given the following equations $$ Y=x_1\beta_1+\epsilon_1 $$ $$ Y=x_2\beta_2+\epsilon_2 $$ Where $Y$, $x_1$ and $x_2$ are all normalized, and that $x_1$ and $x_2$ are correlated with Pearson ...
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1answer
119 views

Trust of coefficients of Logistic Regression

I use logistic regression to model the probability of an event and all of my features are categorical variables. Note that some values of the categorical variables are more frequent than others. The ...
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30 views

Counter intuitive result from logistic regression

I am looking at how well test scores can predict disease status (case/control). There are 6 tests total, A, B, C, D, E, F. And for tests A-E, a higher score is worse (i.e, a higher score is associated ...
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96 views

Interpretation of continuous variable in dummy-continuous interaction

Similar questions have been asked before, but all of them focus on the dummy or interaction term. Say run an OLS regression on the model: $\ln( housePrice )= \beta_1 \times pollutionLevel + \beta_2 ...
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1answer
55 views

Multiple Linear Regression coefficents

I'm doing a linear regression, in R. The values are like this - ...
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1answer
63 views

Confused with SPSS ordinal regression output

I'm a bit (actually, totally) confused with SPSS ordinal regression output. Let say we have dependent variable score=1,2,3,4,5 (higher is better) and one predictor gender=male,female. We run Ordinal ...
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20 views

Standardized Coefficients and Partial r

Ive looked over a few of the posts here on regression coefficients and partial regression coefficients but haven't seen an answer to this question, which maybe easily inferred from the other answers ...
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39 views

Covariance of many simple regressions

Assume we have a true model of $$Y=X\beta+\varepsilon,$$ where $Y$ is some outcome , $X$ is a $1\times p$ vector of covariates which have a (non-diagonal) variance-covariance matrix $\Omega$, ...
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40 views

Is it appropriate to conclude the relationship “does not matter” because the regression coefficient is not significant?

Many papers (e.g. apps.washingtonpost.com/g/documents/national/does-the-amount-of-time-mothers-spend-with-children-or-adolescents-matter/1490/) try to claim an insignificant regression coefficient ...
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18 views

Significant digits for curve fit to numerically generated data

Say that I fit some data with some model, for instance a linear function $y = mx+b$. What is the proper way to report the fitted coefficients and the goodness of fit? Specifically, if I do the fit in ...
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18 views

Worryingly Huge Coefficients with Regression Discontinuity Design

I am running a regression discontinuity design for a project in the early stages. I'm unable to share the data or printouts at this point, for which I apologize, but hopefully the general issue I'm ...
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69 views

Interpreting what this means in a paper - significantly different at the .05 level? [duplicate]

I am having a hard time interpreting what something means in a paper I'm trying to get through. If you care, this is the paper: Gender Differences in the Effect of Education on the Slope of ...
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15 views

Cox/ Binomial Regression: How to reconcile Non-significant model with significant IVs

I'm been performing some survival and regression analyses corresponding to an event of interest being death or a certain surgical procedure, namely a shunt revision for pediatric neuro-surgical ...
2
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1answer
28 views

Why do we make a F-Test rather than a Beta-Test in ANOVAs?

When one performs an ANOVA, (s)he always end up calculating the observed F-ratio and comparing it to the appropriate F-distribution. From this post, I discovered that the coefficient of correlation ...
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262 views

Why do my p-values differ between logistic regression output, chi-squared test, and the confidence interval for the OR?

I have built a logistic regression where the outcome variable is being cured after receiving treatment (Cure vs. No Cure). All ...
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23 views

Does the sign on a non-significant IV coefficient matter?

I have a logistic regression where I am forcing some IVs into the model. I am getting the "wrong sign" i.e. contrary to what is expected, but the association is not significant. Does the sign matter ...
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2answers
49 views

Variance of slope

I have a bunch of data that I fit a linear regression to, and now I need to find the variance of my slope. Is there an analytical way to get this? If an example is necessary, consider this my data in ...
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1answer
41 views

Transformation of regression model to estimate sum of coefficients

How can the model $y=\beta_0+\beta_1x_1+\beta_2x_2+e$ be transformed so that it estimates the sum of $\beta_1$ and $\beta_2$, that is, $\beta_1+\beta_2$ is a coefficient in the new model?
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23 views

When adjusting for X1, have we adjusted for X2, to the extent that X2 is related to X1?

I've just read Elizabeth Stuart's paper on matching methods (http://biostat.jhsph.edu/~estuart/Stuart10.StatSci.pdf), which I find very informative. She discusses propensity score methods and the ...
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42 views

Standardized Regression Coefficients for categorical interactions: lm.beta() vs. regressing standardized variables

I am working with a regression model from which I would like to compute standardized regression coefficients. I am writing primarily regarding an observed discrepancy between coefficients obtained by ...
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1answer
50 views

How to decide whether a variable belongs to a linear model?

I have a set of inputs $x$ and noisy outputs $y$. I think that either $$y = a_0 + a_1 x$$ or $$y = a_0 + a_1 x + a_2 x^2.$$ How can I determine which model was more likely to have generated the data? ...
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109 views

Can logistic regression be modified to predict a distribution, not just point-estimate? Other ways to learn a beta distribution from binary events?

Currently I'm using high dimensional logistic regression to predict the probability of a rare event. I use this probability for both ranking and for other calculations which need it to be ...
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1answer
32 views

Where does the correlation come from in the regression coefficient equation for simple regression

In simple linear regression. $\beta = \frac{Cov(x,y)}{s_x^2}$. This is often written as $\beta = r_{xy}(\frac{s_y}{s_x})$ Where does the correlation come from in this equation? From my understanding ...
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3answers
234 views

In linear regression, what does $\beta_1 = 0$ really mean?

If granted omniscience and we know that $\beta_1$ in a multiple linear regression model is truly 0, what does that mean in words (and math notation)? The model is: $Y = \beta_0 + \beta_1X_1 + ...
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16 views

How can I work out the response effect for categorical coefficients in a generalized linear model?

I have a set of different algorithms I would like to test on a set of different data. Running one algorithm on one datum gives a performance score. This score is log-normally distributed, and ...
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147 views

How to manually calculate dfbetas

I am trying to replicate what the function dfbetas() does in R. dfbeta() is not an issue... Here is a set of vectors: ...
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11 views

Comparing regressions: usual regressor vs regressed-out regressor

I'm comparing the regression coefficients between 2 models: Model 1: $$ Y = \beta_1X_1 + \beta_2X_2 + u $$ Model 2: $$ Y = \beta_1'X_1' + \beta_2'X_2 + v $$ where $X_1' = ...