Questions tagged [regression-coefficients]

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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878 views

Using a zero slope coefficient predictor variable in multiple regression

I ran multiple regression with three predictor variables, which according to the theory I am using, should all predict the dependent variable. However, one of the variable's partial plot shows what ...
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1answer
13k views

What does subscript i mean in statistics in this context (table with values included)?

This has been driving me nuts for hours. I cannot find information anywhere on the internet on what the formulas in the upper-right two cells mean. The i subscript is throwing me off.
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87 views

What happens when switched from more aggregated to less aggregated unit in ecological regression

Sample state data State Percent_ethnicity=1 Percent_voting=1 A 20% 60% B 56% 65% Sample city data <...
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1answer
659 views

Significant correlation but in regression analysis Beta is insignificant. How come? [duplicate]

I have 3 IV's and they are significantly correlated with DV, but when I run regression one of the IV's Beta value turns out to be insignificant. What might be the reason of this?
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256 views

What exactly is the critique in this regression?

Warning: I might be forgetting basic statistics here. Please edit title if it can be improved. This paper, seemingly summarized in the fancy ZUI slideshow here, points out a possible "critique" in ...
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1answer
402 views

Multinomial regression interpretation SPSS [duplicate]

-- start reading from the edited part -- When running a multinomial regression the two values we are really interested in are the values 'B' and B(Exp)'. Let's say we have (fictive numbers): B: ....
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2answers
118 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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1answer
4k 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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1answer
108 views

Interaction effects and insignificant main effects - Back to basics

Imagine the following regression model: $\text{Abnormal Returns} = b0 + b1*SENT + b2*SIZE + b3*SENT*SIZE + e$ SENT is a standardized variable. SIZE is equal to 1 for "uncertain" firms, and 0 for ...
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1answer
28 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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1answer
100 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 Experience-...
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345 views

Java and R: Least Squares Coefficient Estimation - Start at time Zero?

This is the data set I have: vector <- c( -7.459981, 13.26651, 12.10128, 2.380662, 26.42393) Doing an estimation of the coefficient with a linear regression ...
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1answer
717 views

Running all possible additive combinations of a linear model and averaging the coefficients

I have nine predictor variables and one response and when I run a linear model in R I'm getting negative coefficients and non-significant p-vales for essentially all the estimates. I've examined the ...
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1answer
715 views

Multiple Regression - Converting Standardized Coefficients to Unstandardized

I recently performed a multiple linear regression using a standardized set of data, and I was wondering if it possible to convert the standardized coefficients from the regression into usable ...
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1answer
199 views

Simple linear regression and sampling

I have a small dataset (60 elements) for which I fit a simple linear regression model, and obtain a small coefficient of determination ($R^2 = 3\%$). I'm a beginner in statistics so I'm trying to ...
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2answers
2k views

Positive coefficient but negative marginal effect in mlogit

Is it plausible to have a positive coefficient with a negative marginal / impact effect after running multinomial logit model?
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1answer
168 views

Imputation model: Pooled model is insignificant. How to interpret?

I have ordinal data on three IVs ranging from 1 to 5 as below: IV1: Not at all Important - Very Important IV2: Not at all Satisfied - Very Satisfied IV3: Performs much Worse - Performs much better ...
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1answer
129 views

Issues in estimation and plot

I am learning adaptive filters and testing the performance of using Least Squares and Kalman filter for parameter estimation for $y = X + \text{noise}$. The model is autoregressive AR(2) model $$y(t) ...
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1answer
120 views

Multivariate model and large regression

I am not familiar with the concept of multivariate model and just learning about regression model. I am familiar with Autoregressive model and Moving Average. Multivariate regression model provided ...
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1answer
2k views

What do the coefficients of the crossproduct of regression mean?

How can I interpret the coefficients of the crossproduct of each of the following codes? What do they mean? How can I deduce that they correspond to our expectation? Also which crossproduct is correct?...
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1answer
647 views

R Interpret coefficient from Survreg(dist=“gaussian”) [closed]

I was wondering if anyone could help me on how to interpret the coefficient from an analysis I have carried out in R (survival package). The data is right ...
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1answer
384 views

coefficients and p-value in logistic regression

In logistic regression, I have a variable with larger coefficient and larger p-value and another variable with smaller coefficient and smaller p-value. If use p-value then the latter one is more ...
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1answer
1k views

R: Explanation of a multiple linear regression summary [duplicate]

I am quite new with R and while i am able to perform the basics i am not yet able to understand the output results. For example: summary(lmodel) generates the ...
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1answer
45 views

data prediction by regression or better ways

I am working on data prediction. Given data of a random variable $X$ and $Y$, find out how to predict $Y$ from $X$. I know how to do it by linear regression, $\hat{Y} = kX + b$. But, here, $X$ is ...
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1answer
1k views

Finding an optimal value for parameter given other parameters

I am looking for a way to find an optimal value among several combinations of values. The data looks like this: ...
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1answer
73 views

Coefficients by group

I have a data set with 8 different treatments and there is unequal number of observation within each group. I'd like to calculate regression coefficients for each group but I can not do it in other ...
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2answers
1k views

How can I set a maximum and minimum level for a dependent variable?

I have to make sure that a dependent variable I explain using linear regression ranges between a minimum of 0% and a maximum of 30% (it is an investment weight in a portfolio). How should I proceed ?
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1answer
197 views

Interpretation of the regression coefficient of a proportion II

Following question: Interpretation of the regression coefficient of a proportion type independent variable In my model I have a log dependet variable. As indenpendet variables I have one proportion $...
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1answer
557 views

How do sampling error, measurement error and specification error affect regression coefficients

Can anyone answer the question or direct me to the proper resources - ESPECIALLY for sampling error effect on the coefficients? How would the coefficients be affected if the independent variables came ...
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1answer
351 views

Mean regression factor scores and attributes cross tabulation yields. Why are all expected signs reversed?

I ran a factor analysis on 20 reasons for purchasing 4 different goods. These are ranked on a Likert scale from 1 to 5 with 5 being "extremely important", 4 "important", etc. I extracted 4 factors ...
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1answer
734 views

How to compare regression coefficients across three FGLS models in Stata?

I have a longitudinal dataset, so for each company different year observations. The time period of the dataset is 1993 to 2008. I tested a FGLS model on the whole dataset. Now I want to test the FGLS ...
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5 views

Interpretation of negative binomial coefficients

I'm reviewing a manuscript and the authors are using a negative binomial regression. They interpret the results using probabilistic language ("more likely"). My understanding is that this is ...
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0answers
18 views

Logistic Regression, converting to weights [closed]

I have logistic model, which has coefficients between 0 and 1. However, the sum of all coefficients doesn't lead to being to one. I understand we can't normalize the logistic coefficients and use them....
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2answers
25 views

Confusion regarding Least Square/Maximum Likelihood estimators under a restricted intercept?

I'm a bit confused regarding how intercept restrictions impact slope estimators in a simple linear regression. An example: $$H_0:\beta_0=0$$ $$H_A:\beta_0\neq 0$$ I simulated a variable $y_i$ as: $$...
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Interpretation of regression coefficients after power transform (possibily with polynomial transform and PCA) [duplicate]

In general I standardize my features before regression by subtracting the mean and dividing by unit variance: $$ \hat{X} = \frac{X - \bar{X}}{Var(X)}$$ With this basic standardization, interpreting ...
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11 views

Back-transformation of coefficients in a log-log model, and a model with a boxcox transformed y

There's a number of posts out there on back-transformations but none that I've been able to use to answer this problem, internet searches are returning surprisingly little on the issue of back-...
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1answer
18 views

Interpreting linear regression with endogenous treatment effects

Using stata (with weighted survey design) I ran the following, where logwage is the log of wage. The log was taken because wage was not normally distributed. There is also information about the ...
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3 views

PLSR algorithm and terms like weight, loading, score

Can anyone suggest good resources to understand Partial Least Square Regression(PLSR) algorithm and the terms associated with it like weight, score, loading. I am doing a project on soil macro-...
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1answer
17 views

Comparing coefficients in logistic regression with curvilinear effects

I’m conducting a multiple logistic regression with 3 predictors (x, y and z). A Box-Tidwell test suggested that the relation between x and the dependent variable is not linear on the logit, so I have ...
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0answers
21 views

Adding a new predictor to an existing (estimated) regression model?

First, I should point to (at least) two similar questions (here and here); however, I could not find an answer fitting my needs there. I have a set of fixed covariates and a large number of (~ 1,000,...
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1answer
19 views

the meaning and metrics of beta coefficients in glmnet Ridge regression

I have done a ridge regression using the 'glmnet' function in R. Then, after finding the optimal lambda parameter, I checked what are the predictors' beta coefficients by extracting glmnet.fit$beta ...
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10 views

Interpret coefficients in L_k norm regularisation

Assume I want to do some regression on customer life time value. I have three features: age, income, height (denoted x1,x2,x3) and their coefficients ...
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11 views

How to construct ANOVA table only using the output from summary()?

Without using any other R function, how to calculate ANOVA table only using the output from summary()?
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1answer
20 views

GLM coefficients from caret - Machine Learning

I have a quick question I can't seem to find a good answer to, so I hope this makes sense and please let me know of any important information I may leave out. I've been using the machine learning ...
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0answers
18 views

Could the first differences estimator be a better choice than fixed effects, regardless of serial correlation and heteroskedasticity?

TLDR: Is the first differences-estimator a better choice than a fixed effects model for panels where the demeaned dimension is categorical with three categories, where two of them usually have no ...
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1answer
20 views

Total effect of main variable and it's interaction with dummy

I am going to estimate the following model: y=constant+b1(X)+b2(X)(Dummy) We have daily data from 1990 to 2000. Dummy variable is equal to one for the daily data of year 2000, else zero. b1 is the ...
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21 views

Interpreting a low phi-coefficient, but a high regression correlation coefficient

I'm conducting statistical analysis on two categorical binary variables. My phi-coefficient yields only 0.09 at a 0.01 significance level. However, when I conduct multiple logistic regression on the ...
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0answers
16 views

I am comparing the sex ratio of pheasants across Study Areas, (10), Release sites (26), and Years (13)

I am using Binary Logistic Regression and comparing Models using AIC. The Model is: sex ratio= study area + release site + years When I count the number of Parameters (K) in the Model -do I count ...
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14 views

What would be a good method to compare the results from my model to actual measurement data?

I have a complex physical model of an engine and I get certain outputs for a given set of inputs. However, these outputs are of course, not exact and deviate from the physically observed values for ...

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