Questions tagged [multiple-regression]
Regression that includes two or more non-constant independent variables. Also known as multivariable regression.
4,589
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Calculate Standard Error of Dependent variable using Multiple Linear Regression Output
Title says it all. I'm trying to calculate the SE of an independent variable using values from MLR.
I have 5 predictors, their coefficients, their SE, t-statistics, and p-values.
I also have the R^2, ...
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8 views
Problem with a covariate in multiple regression
I hope someone can help me!
I am conducting a multiple regression analysis with 4 predictors selected via stepwise regression. One of them had not a bivariate correlation with my dependent variable ...
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2answers
24 views
Trying to find a proper regression model for non-negative dependent variable
I'm trying to build a regression model predicting passenger numbers on trains using a number of different variables. Originally my plan was just to do a linear regression, but the issue is the model ...
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30 views
Proof that $Var(\hat{\beta_j}) = \frac{\sigma^2}{nVar(X_j|all \space other X_i)}$ in Multiple Least Squares regression
How is it possible to prove that $Var(\hat{\beta_j}) = \frac{\sigma^2}{n \cdot Var(X_j|all \space other X_i)}$
where $j \geq 1$ (I am interested mainly in slope estimates) and $\hat{\beta_j}$ is the ...
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8 views
Non-significant regression model (MLR) with significant predictor
I'm having trouble with interpreting some results I've found. In order to test my hypotheses I've conducted four analyses.
My hypotheses were:
X1 positively predicts Y1 and Y2
X2 does not predict Y1 ...
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17 views
Pairwise deletion in regression
I'm conducting a research on R to study how variables like coal, wind, solar, hydro generation, demand and weather variables (independent variables) affect the energy price (dependent variable) for ...
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17 views
How to interpret interact_plot for categorical x continuous interactions
I'm wondering how to interpret interact_plot plots for categorical x continuous interactions. Here's a toy example to illustrate:
...
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9 views
How can I identify if I have enough variation in my variable to identify an impact?
My data is panel and its on employee attendance and weather. I observe employees daily attendance for about 2-3 years. So I have a panel at the daily level for each employee.
I have a binary X ...
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8 views
Update an existing ordinary linear regression with new data and another covariate
I am studying a case on a topic that was studied a while ago, related to food technology. To simplify the question, let's say that there are old OLS models that relate this property ($Y$) in certain ...
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9 views
Multiple Regression Model: Find Beta 1 hat via OLS. Find Beta 2 [closed]
everyone!
I'm completely new to statistics and currently learning the multiple regression model. Could anyone look through this and explain how I get to solve it. It's extemely important to me that I ...
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7 views
How to do hierarchical regression with interaction in R (see example) [closed]
I'm trying to do a hierachical regression in R like it's usually done in psychometric research.Where I first make a model with a main effect and then make a second model with an interaction effect. ...
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9 views
Multiple Regression Extreme Values in all Covariates
In multiple regression:
If we have a data set with covariates having extreme values, the max value of the covariate is around 10 to 14 times the mean value of that covariate. This is occurring for all ...
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16 views
Interpreting the following multiple linear regression model
I'm having difficulties trying to interpret the coefficients of my linear model.
Background:
lm(encounter_rates ~ year + pland_changes + regions)
I've run a ...
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1answer
25 views
Multiple regression models in R [closed]
If I have data that include:
The gender variable gets the value "1" for a woman and "0" for a man.
The variable hours is the average number Of weekly working hours
The variable ...
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8 views
How do you determine which variables to transform in linear regression?
Are there any tips as to how to diagnose the residuals of your regression model. For example, I have a residual plot that is both skewed and non-linear.
When you have many predictors, is there any ...
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10 views
Interpreting the coefficients when a ln10 transformed DV is predicted by a mixture of ln10 transformed, dummy (0 & 1 coded), and continuous IVs [duplicate]
I have a multiple regression equation that reads as follows:
ln10(DV) = 0.437 + 0.394(ln10(IV_1)) + 0.061(IV_2) - 0.145(IV_3)
I performed the ln10 transformations for the DV and for IV_1 to get around ...
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7 views
How would you transform a percentage dependent variable to fit a logistic regression? [duplicate]
I have a outcome variable that is a percentage (proportion). According to this, I should probably use a logistic regression: What are the issues with using percentage outcome in linear regression?
My ...
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1answer
25 views
Developing Risk Scores from Cox Regression model?
A simple question on the development of risk prediction models from Cox regressions.
Suppose, as an example, that I want to create a risk score for 1-year mortality in patients with cardiovascular ...
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5 views
Comparing mixed effect models using deviance statistics - comparing model 1 vs. 4 instead of 1 vs. 2, 2 vs. 3, etc
I am relatively inexperienced with mixed effect models and trying to build a model to fit my outcome of interest. I have read and followed along with chapter 4 of Singer & Willet (2003), as well ...
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1answer
26 views
Interaction of Gender and Income categorical variable
I ran the following model, with exam scores in science as my outcome variable, and parental income group divided into 5 groups and a binary gender variable with the results below:
...
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1answer
19 views
Comparing significant differences between a linear regression on same data coded as ordinal or interval
I'm running linear regressions in R on some survey data that was delivered as Likert-scales. In R, I can code them as factors (to represent them as ordinal data) or numeric (to represent them as ...
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25 views
What is the recommend function for Ridge regression [duplicate]
The following question is an answer for why lm.ridge and glmnet results are different and how to solve that. My question is ...
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8 views
What test statistic for the hypothesis that early events affect future events?
Consider you observe a series of events occurring over time where an event's time is denoted by $t_i$ ($i=1,2,...$). That is, you observe a vector $t = (t_1, t_2, ..., t_k)$ for $k$ events. Your ...
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1answer
19 views
Should I include month of interview dummies in regression?
I have a quick question regarding dummies for a regression that I am running.
I am running regressions of responses to a survey question about health on a vector of independent variables (e.g., ...
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1answer
40 views
Separate Bonferroni corrections for multiple categories
I have a study in which we are looking at healthcare costs and utilization by patients with a disease vs. healthy controls (HC), as well as by different stratifications of disease (severity, ...
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1answer
56 views
Setting up a linear regression: plant height as a function of time period and soil pH
The following is from Hoff's "A First Course in Bayesian Statistical Methods" book.
The data set tplant mentioned above appears below.
I am trying to use an ordinary least squares to fit a ...
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11 views
Strange, symmetric suppression between 3 IVs in multiple regression?
I have encountered an interesting phenomenon while working on some data derived from a(n admittedly badly constructed) questionnaire by a colleague, and I have no idea what to make of it ...
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0answers
17 views
Sequential Bayesian Linear Regression with Diagonal Covariance
The standard update rules for a sequential Bayesian linear regression are well-known (heck, they're even on wikipedia: https://en.wikipedia.org/wiki/Bayesian_linear_regression). However, in large ...
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2answers
52 views
Meaning of θj in equation for partial derivative of MSE
The equation to find the partial derivative of a cost function with respect to a parameter θj is given in the book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow:
$$
\frac{\partial}...
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1answer
30 views
Meaning of a varaible for calculating the partial derviative of MSE cost function
The equation to find the partial derivative of a cost function with respect to a parameter θj is given in the book 'Hands on Machine Learning with scikit-learn, ...
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39 views
Is this regression model valid X/Z = B0 + B1*X + B2*Z? [closed]
In other terms can I explain a variable with the others variables that are used to compute this variables?
What are the implication for my model?
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1answer
33 views
What regression approach would suit zero-inflated data that is censored at a fuzzy threshold?
Monthly grid-cell burned area estimates are (almost) lognormally distributed, censored at a fuzzy threshold and zero-inflated. I want to predict burned area from weather etc. About 40% of the ...
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1answer
17 views
When you dummy encode for logistic regression, how do you determine the feature importance for the reference group?
Say you have an IV that can be k different categorical values, and you are trying to do logistic regression. To avoid multicollinearity, you dummy encode the IV into k-1 variables, with one of the ...
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4 views
Difference between PERMANOVA and Multiple Regression on distance Matrices
I am a newbie in statistics so the math part of these 2 tests might not be crystal clear. But it seems that they are quite similar if you try to analyze e.g. how 4 variables explain the dissimilarity ...
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13 views
Interpretation interacting dummy variables regression
Suppose I have a panel dataset with a time and cross-sectional dimension. I split the time-dimension into three intervals (Interval A, B and C). Furthermore, I split the cross-sectional dimension into ...
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1answer
74 views
Upper bound for variance of $\hat{\beta}$ in multiple linear regression
The variance of the beta estimator in an ordinary-least-squares multiple linear regression to express $Y$ as a (linear) function of $X$, $\hat{\beta}$, can be expressed as (knowing $X$ and $\sigma^2$ ...
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15 views
How to interpret regression results when there are many dummy variables, not many catergories in one dummy variable
I am confused my regression results.
My data is something like this.
I want to see whether the presence of these six species would have significant effects on TD. So, I make every of them be dummy ...
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1answer
18 views
Why p-values are inconsistent when applying model on subsetted data versus using interaction terms
I have the following negative binomial GLM, where "group" is either Control or Experimental and "count" shows the number of times patient came to hospital.
...
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1answer
35 views
Which plot to check for heteroscedasticity in a multiple regression model
I have a linear model like:
Reg.Model = lm(Y~X1+X2+X3, data=DF)
If I want to check for the presence of heteroscedasticity using a plot, should I plot the residuals ...
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1answer
20 views
multiple regression model with multiplication between independent variable and a dummy variable
I was asked to build a linear regression model with multiplication, in the iris dataset in R.
$Sepal.Length_i = \beta_0 + \beta_1 \cdot Petal.Length_i \cdot Species_i + \epsilon_i$
now I know in R , ...
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0answers
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How to compare a Linear Regression’s Coefficients with the Coefficients for its Subgroups using Standard Error?
Assume a linear regression model has been made of an item’s overall utility value, and elements like durability and color availability have statistically significant coefficients in the overall value ...
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14 views
How do I model 2 variables that both affect eachother?
I am trying to model the relationship between tourism traffic and the proportion of coral reef bleached over time. I noticed that an increase in tourism will increase the proportion of reef bleached ...
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1answer
39 views
Moderation (interaction) - Cannot use moderation if a moderator has an effect on independent variable?
I have a following simple moderation model:
$$ y = b_0 + b_1x + b_2m + b_3(x \times m) + e $$
However, previous studies have also found that $x$ has a effect on $m$:
$$ m = a_0 + a_1x + u $$
If $x$ ...
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7 views
Method towards calculating 95% confidence intervals with 2 predictors
I'm trying to calculate a confidence interval for the slope of my x1 predictor.
I'm given the RSS in addition to the attached info.
Is my next step finding my estimated standard deviation in order to ...
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34 views
Using VIF, Interaction Effects, polynomial associations for feature selection in multiple linear regression
Is there a guide, tradition, or accepted practice on what to take into account and in what sequence between VIF, interaction effects, variable transformations and polynomial associations when ...
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17 views
What is the best method for analysing data from 10 countries, over ten years with ten variables?
I am undertaking my dissertation and I am analysing the effect FDI has on economic growth in Southeast Asian countries. I have data from ten variables for each country (10 in total) and have gathered ...
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Bayesian multivariate regression
I am trying to solve the below multivariate regression problem by building a fully Bayesian model-
\begin{align*}
\mathbf{Y} = \mathbf{X}\mathbf{B} + \mathbf{E}
\end{align*}
where $\mathbf{Y} \in R^{n\...
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0answers
13 views
Interpreting coefficients of several multiple regression models
I have a dataset containing last 4 years of sales data for various categories of items. I've built one regression model for each category to explain 'the reasons' behind different performances. I've ...
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1answer
20 views
Nested models in linear regression
I am getting confused in defining if models are nested. I know the basics that the reduced model can be derived from the full model by removing terms or setting terms to 0.
But what about a case like ...
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23 views
Regression coefficients residuals interdependence? [closed]
I would like to check and describe the dependence between the errors in the regressors of a regression model. Let A and B be the errors, I created the following plots:
My question:
Looking at the ...
