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.
1,350
questions
0
votes
0answers
18 views
cents per gallon to gallons per person - regression intepretation
Equation: fuel = B0 + -7.441gatax
fuel: motor fuel uses in (gallons per person)
gatax: state gas tax in (cents per gallon)
How would you explain a 1-unit increase in the gas tax?
thanks for any ...
2
votes
1answer
24 views
Calculating the standard errors of the standardized regression coefficients from an article
For a systematic review I want to calculate a confidence interval around the standardized regression coefficients for a multiple linear regression model, e.g. using the following effect size ...
0
votes
0answers
11 views
Combined Versus Split Regression Model Coefficients
I am working on a semi-unsupervised model, where the model itself takes coefficients of a regression as inputs. I have a criteria for separating the data within one regression (indicator variable), ...
0
votes
0answers
9 views
Can you use the inverse normal probability of a variable as the dependent variable? [closed]
And then regress this variable on your independent variables? And then obtain the normal distribution function on your estimated values and use this as your estimated value? Is this econometrically ...
0
votes
0answers
6 views
Find highest scoring yet most consistent performer
I have several measurements with a mean and a standard deviation (but I believe that the coefficient of variation is more useful here).
For example:
A: Mean (in regards to the total): 90%, CV: 25%
...
-1
votes
0answers
22 views
Help in Maximum Likelihood Estimation for ARIMA Model in R
help in maximum likelihood estimation I used seasonal arima model on my univariate data set with order
...
0
votes
1answer
31 views
Linear Regression with coefficient of a, b, c and d?
First I am a beginner and am trying to understand linear regression. I was reading an article and saw a formula:
...
0
votes
1answer
53 views
lme4 mixed model output coefficients seem incorrect
I have some data for carbon assimilation vs tree size for a range of tree species. I'm running a mixed model analysis using lme4 in R, with the random effect being ...
0
votes
0answers
12 views
Calculating simple effects from standard regression output
This question seems so basic I am almost embarrassed to ask it, but my need for clarity has finally exceeded my need to pretend like I know everything.
I am testing the effect of prior training on ...
2
votes
0answers
115 views
+50
Equivalence of ANCOVA and alternative model
Consider an RCT with individuals i in 2 arms (group, with 0 = control and 1 = treatment) in which one metric outcome (score) is collected at baseline (pre) and after some treatment (post).
In an ...
0
votes
0answers
8 views
How can I compare incremental-r2 between groups?
0
I have a dataset (n=6000) of individuals belonging to three different ancestry groups (african (n=2000), native american (n=2000), european (n=2000)). I am studying how well a predictor (x) ...
2
votes
1answer
66 views
+50
Testing if coefficients are statistically significantly different across models
I will be building two zero-inflated negative binomial (ZINB) regression models, where each model is aiming to predict different disease count outcomes based on the exact same independent variables ...
0
votes
1answer
14 views
R choose which element of factor variable to throw out to produce only positive coefficients [duplicate]
How to manually choose which element of factor variable to throw out? Or how to automatically throw out the element with the least coefficient so that in the final model we have all the coefficients ...
3
votes
0answers
39 views
estimation of polynomial regression: bootstrap approach
Assume, one deals with polynomial regression, i.e.
$$
y_{i} = \beta_{0} + \beta_{1}x_{i} + \beta_{2}x_{i}^{2}+ \dots + \beta_{m}x_{i}^{m} + \varepsilon_{i},
$$
where $i = 1, \dots, n$, with $m < n$...
0
votes
0answers
19 views
Difference in regression coefficients of sklearn's LinearRegression and XGBRegressor
Using the Boston housing dataset as example, I'm comparing the Regression Coefficients between Sklearn's LinearRegression() and xgboost's XGBRegressor().
For XGBRegressior, I'm using ...
0
votes
0answers
41 views
Linear regression $Y=X\beta+e$ with random coefficients $\beta$
Consider a linear regression model $Y=X\beta_0+\epsilon$. Here $Y$ is the response random vector of length $n$, $X$ is an $n\times p$ matrix, $\beta_0$ is a constant vector of length $p$, and $\...
0
votes
1answer
23 views
How to find coefficients for Logistic Regression [duplicate]
How do you find the coefficients for logistic regression?
Is it a case of just transforming the samples from the dependent variable and preceding to fit it like a linear regression?
0
votes
0answers
43 views
Normal equations for multiple linear regression using covariance matrix [duplicate]
I find in many textbooks the normal equations for multiple linear regression:
$$\hat{\beta} = (X^\prime X)^{-1} X^\prime y$$
However, I am interested in estimating the regression coefficients using ...
0
votes
0answers
30 views
Bootstrapping logistic regression coeffs with z-scored predictors in logistic regression
Hoping someone can help clarify why there is a discrepancy in regression coefficients when applying bootstrapping to z-scored vs. raw data. There is probably a simple explanation but in all my ...
0
votes
0answers
32 views
Correct interpretation of coefficient estimates from GLM on binary outcome data [duplicate]
I'm currently analysing an experiment where animals were presented with a stimulus under two different treatments (Po & Br) ...
0
votes
0answers
32 views
Different Formulas for the Standard Error of Regression Coefficient
Premised that I am no expert in stats or algebra (but I am trying to learn), I have found these two different formulas for the standard error of the regression coefficient.
\begin{align}
\...
0
votes
1answer
29 views
Regressions - variable effect
This is more of a theoretical question than concerning a specific data set.
Say that I have a dependent variable Y and want to check if 4 different explanatory variables X1, X2, X3 and X4 has an ...
2
votes
0answers
32 views
Test for difference of coefficients in two logit regressions
I have the following problem. I have a sample of $n$ observations and divide it into two non-overlapping subsamples with size $n_1$ and $n_2$ correspondingly. Then I run logit regression for both ...
6
votes
3answers
989 views
Negative relationship but regression analytics gives positive correlation coefficient
I've been trying to look for a question like this but I simply see positive correlation coefficients. I'm new to this so forgive me if I'm not really familiar with the terms.
I'm doing an analysis on ...
7
votes
1answer
83 views
The lines on my scatterplot for ANCOVA results doesn't look right, personal error or model error?
I ran an ANCOVA model, to test the effect of treatment on the relationship between two continuous variables (elephant number and plant density) - please see more details in my last question (What ...
3
votes
1answer
59 views
Why is odds ratio used when interpreting logistic regression?
I am fairly certain when interpreting logistic regression output, the odds ratio should be used instead of the estimated coefficients; however, I am unable to figure out why this is the case.
So my ...
1
vote
1answer
24 views
When using Lasso and calling coefficients (.coef_) which is the coefficient of the constant? [closed]
By calling .coef on the Lasso model built, there are only numbers corresponding to the coefficients.
These coefficients are supposed to match, say, the columns of the pandas dataframe given as input. ...
0
votes
0answers
9 views
Variable Importance sorting by absolute value of x or fully standardized coefficient?
I am looking at the output of a linear regression model and would like to sort the IVs by feature importance. In this case I want to use the absolute value of the standardized coefficients since my ...
2
votes
1answer
36 views
Comparing Regression Coefficients from a “log-log” to an Alternative De-meaning Procedure
Consider two regression models:
$log(y_i) = \log(x_i)\alpha + \epsilon_i \,\,\,\,\,$ (Model 1),
$log(y_i) = (\frac{x_i}{\overline{x}})\beta + \varepsilon_i \,\,\,\,\,\,\,\,$ (Model 2),
...
3
votes
3answers
127 views
Is there a difference between $\beta$ and $\theta$?
I've seen both $\beta$ and $\theta$ used to indicate model parameters in different publications. For example, Andrew Ng uses $\theta$ in his ML course and Gareth James et al use $\beta$ in ISLR.
My ...
0
votes
1answer
18 views
Multiple regression when the dependant variable is unmeasured or hidden
Say I was measuring the individual performance of each of a group of athletes every week. I measure things like running speed, jumping height, grip strength etc.
I want to use these scores with ...
6
votes
1answer
81 views
Where are the Wald p-values and where are the LRT ones in the resulf of mixed models? [closed]
I read, that there are many methods of determining the degrees of freedom, thus calculating the p-values for fixed effects in mixed models. I read, that the worst is the Wald test and the Log-...
1
vote
1answer
39 views
Linear Regression: P-values of t-test of significance of regression coeficients are same as p-values of F-test about submodel
Suppose we have regression problem:
$$Y = \beta_{0}+\beta_{1}X_{1} + \beta_{2}X_{2} + \epsilon \text{, } \epsilon \sim \mathcal{N}(0,1),$$
where $X_1 \sim U(0,1)$,$X_{2} \sim U(1,2)$, and we suppose ...
0
votes
0answers
20 views
Interpret Coefficeint as change in Percentage-point or Percentage
Having carried out the regression below, I'm struggling to determine what the correct interpretation of the predictor variable would be.
Given that the dependent variable is binary, where 1=...
0
votes
1answer
23 views
What is a reason that in Lasso Regression we can force all coefficients positive & intercept =0?
I have a regression problem where I need all coefficents to be positive and the intercept to be zero. I can do this in sklearn but i don't understand how the algoritm can force this conditions through ...
2
votes
0answers
61 views
Marginal means vs. marginal effects. What is the difference?
In R, there are two packages: emmeans and margins. The first implements the LS-means known from SAS, here called estimated marginal means, the second implements the margin command from Stata. I ...
-1
votes
1answer
29 views
In which paper did this formula appear? [closed]
I want to use this formula in my paper, but I don't know which paper or book to cite. Can anyone tell me which paper I should cite?Thank you!
The formula is related to linear regression.
$\hat{Y}_i =...
1
vote
0answers
29 views
Relating Two Derivatives (and Elasticities) of a Log-Log Regression
Consider a standard "log-log" linear regression model like this:
$\log(y_i) = \log(a_i + b_i)\delta + \epsilon_i$,
where $y$ is the dependent variable, $a$ and $b$ are two independent variables, and ...
0
votes
0answers
16 views
How to interpret coefficients of parametric terms in comp.risk?
I am trying to fit a flexible competing risks semiparametric regression model with the timereg package. My primary goal is to estimate the effect of Z on the cumulative incidence of the event of ...
2
votes
1answer
95 views
Multiple regression and partial correlations with more than 3 predictors
I need to estimate slopes of a multiple regression that has 5 independent variables:
$$y = \alpha + \beta_1 x_1 + \beta_2 x_2 + \beta_3 x_3 + \beta_4 x_4 + \beta_5 x_5$$
The challenge is to estimate ...
1
vote
0answers
25 views
Why do regression estimates provide lower relative error than averaged values?
I am trying to estimate the per-cell protein concentration for some samples. I have performed a series of protein extractions for each of my samples, with each extraction using an increased (and known)...
0
votes
0answers
19 views
Interpreting the Odds Ratio of a logistic regression model
I'm currently working on building a logistic regression model with the aim of predicting whether a given stock index will go up or down the following day. The table below shows the 3 models I've ran ...
1
vote
0answers
24 views
How to identify weak predictors from financial data
I have a financial data.frame that contains quarterly data for each stock in S&P500 - 16 quarters for each stock, a total of 8000 rows. What I am trying to do is to explain 30-day volatility (...
0
votes
0answers
15 views
Using the autohotencoder in PySpark for a linear regression but no reference category
I created dummy variables using the autohotencoder and as I have learned dummy variables you also need to have a reference category. However I have 7 dummy variables for the weekdays for example, so I ...
2
votes
1answer
91 views
R: How to create equation from logistic regression glm() model coefficient estimates? [closed]
I am trying to create a formula from the published glm() model coefficients estimates, i.e. I don't have raw data to reproduce the model. Further, I want to apply ...
0
votes
1answer
21 views
Regression coefficient problem
The question asks that when the case is $X_1 = 1$ (when I am an asian instead of other ethnicity, a dummy variable), then what is the value of $Y$? As the $b_1$ has a P-value much larger than $0.05$, ...
0
votes
0answers
15 views
Insignificant coefficient in a regression
To simplify the question, for example, the interception, which is Beta 0, is +500 and the predictor X1 being 1, Beta1 being negative 100 and other predictors Xi are all 0. i.e. Y = 500 -100 X1.
The ...
0
votes
0answers
7 views
fitting suitable regression model to identify predictors from contingency table
so a study was conducted for some game and the probability of success of the game was noted in a contingency table.
I have a 5x5 contingency table which is age group by task difficulty(split into ...
1
vote
1answer
55 views
Significance test for coefficients of elastic net
I have a 150x41 dataset, on which I performed variable selection and regression with Elastic Net. The response variable is continuous. I'd like to test the significance of the coefficients that I ...
0
votes
1answer
47 views
multiple regression coefficients - Standard error of intercept
I am implementing an R-type summary() function in python with the restriction to exclude use of scientific libraries. (assignment)
I found this https://www.nd.edu/~rwilliam/stats1/x91.pdf material ...
