# multiple-regression's questions - Chinese 1answer

3.207 multiple-regression questions.

### 3 How to calculate p-value for multivariate linear regression

Software packages that calculate regressions sometimes also return p-values. I want to understand how to calculate this p-value by hand. Here's what I think I understand: I want to calculate the ...

### Beta Coefficient range

Is there a table of range for beta coefficients used in multiple linear regression that we can use to interpret if influence is strong, very strong, weak or very weak. Thanks!

### 3 Can I still use Linear Regression assumptions test on a linear model with a Polynomial variable

I have a multivariate linear model (y=x1+x2) which gives me the following results when using R's plot() function: I can clearly see that the Normality and ...

### What is meaning of high AIC value?

I have a query related AIC value. I am getting very high AIC values while selecting multiple regression model, ranging from 4300-4600. Is it possible to get such high AIC values?

### 1 Sample size for multiple regression using G*Power

I am running a study on school children to compare psychometrics in physically active and sedentary children. My IV is physical activity with 2 levels - physically active / sedentary and DV ...

### Likert-scale data as DV… curious as to which regression model to use

I have a 1-10 Likert scale as my DV and five variables as my IV. My IVs include both continuous and categorical variables. I am wondering which independent variables have a major effect on my ...

### 1 Comparing hundreds of regression models in R efficiently [on hold]

I'm working with a data set of housing prices in Seattle from Kaggle.com. I have identified 7 variables that are significant in a linear regression model for modeling/predicting the prices of the ...

### Reifying stepwise regression with additional predictors and hierarchical regression

0 answers, 11 views regression multiple-regression
I have performed (backwards elimination) stepwise regression using some fMRI data predictors to model spectroscopy data as a DV. This has resulted in some interesting models. I now have some ...

### Help analysizing a multivariate regression (cloglog) model using gen mod in SAS

I am having trouble with interpreting the estimates. I took the exponent of the estimate. If it is negative I get a result that makes sense. For example, .55 means X has a 55% less chance to exiting; ...

### 3 Linear regression with interaction SPSS

I have to run a linear regression analysis with an interaction effect of two categorical variables: Modality (audio, visual and audio-visual) Repetition (1x, 2x and 4x) I have already dummified the ...

### 3 Why use Poisson regression for p-values for linear regression?

Byars et al.'s paper "Natural selection in a contemporary human population" includes a multiple linear regression of number of children (LRS, lifetime reproductive success) on several variables (...

### 1 Non-uniform density of observations

0 answers, 19 views regression multiple-regression
I would like to build a regression model to predict an outcome variable, y. Let ymin, ymax be the smallest and largest observed values of y in the dataset. Let ymean be the mean observed value. The ...

### 18 Assumptions of multiple regression: how is normality assumption different from constant variance assumption?

5 answers, 1.642 views regression multiple-regression assumptions
I read that these are the conditions for using the multiple regression model: the residuals of the model are nearly normal, the variability of the residuals is nearly constant the residuals are ...

### 3 Comparing observed and predicted values across several measurements

As a neuropsychology graduate student with some experience in statistics (I'm usually the guy other psychologists come to with statistics problems after trying it themselves but before seeing a ...

### 1 When does the Stagewise algorithm stop

Does the Stagewise algorith stop when the gradient reaches 0? What if the algorithm never reaches the gradient=0, is there any valid criteria to be used to stop it?

### 3 Efficiently add a new predictor to an estimated multiple linear regression model

I want to use forward selection to choose predictors in a multiple linear regression model. If you have a regression with N predictors and want to add another predictor, is there a way to update the ...

### How to show that ols doesn't do well on high correlated predictors

I have here an R example with highly correlated predictors. How can I show that OLS doesn't predict well on highly correlated predictors? ...

### -2 Multi output RandomForest example ? [on hold]

Is there any example of RandomForest with multiple output that can help me understand better how to compute it, whether it is using MultivariateRandomForest library or other ?

### 1 Understanding MLR [closed]

0 answers, 27 views regression multiple-regression
I am just trying to explain to people with very little knowledge of statistic about MLR. I basically Have this question: Why when we have the number of independent variable ($X$) and dependent ...

### 1 Any recommendations on how to analyze categorical data? [closed]

0 answers, 20 views anova multiple-regression
I have been assigned to help create a new sales model. My natural instinct is to try to find trends among current customers within the data that I have been given so that we can more effectively ...

### 2 Multiple regression with a factor variable in R

I'm trying to run a multiple regression on a dataset in R. The structure of the data that I want to use for the regression is as followed (only showing the variables I want to use): ...

### 2 Is the normality of residuals necessary to accept the null model in a multiple regression analysis?

Best-subset regression analysis: I want to test effects of differents ecological variables on my response variable. I am working with function glmulti() of glmulti ...

### 1 Linear Model feature selection - AIC vs ANOVA vs t test

2 answers, 34 views anova multiple-regression t-test aic
Suppose I have a multi regression model, dummy variables and interactions included. How am I suppose to filter through them all in order to choose the best model? I KNOW this question was asked on ...

### 1 Regression model with some regressors depending on other regressors

We want to investigate which variables determine the final grade in a University exam (say Y_2), which can assume integer values between 18 and 32. We think that Y_2 depends on: 1) Personal variables ...

### 1 Must a moderator correlate significantly with the dependent variable (Y) in a moderation analysis?

Must the moderator variable correlate significantly with the dependent variable, if I am to do a moderation analysis (multiple regression)? I have a predictor (X) and an outcome (Y). They correlate ...

### 12 What is the interpretation of the covariance of regression coefficients?

2 answers, 3.224 views r multiple-regression least-squares
The lm function in R can print out the estimated covariance of regression coefficients. What does this information give us? Can we now interpret the model better or diagnose issues that might be ...

### 2 Forecast using multivariate multiple linear regression using R for multiple dependent variables

I'm trying to do predict using multiple linear regression in R. I have been able to do the multiple regression bit, by converting raw data to data table. However, when i'm trying to use predict ...

### Is it wrong to standardise a variable and then centre it for use in multiple regression? [duplicate]

Is it wrong to standardise a variable (e.g. polygenic risk score) and then centre it for use in multiple regression?

### What are the best variables to be used in analysing the performance of a bank using regression analysis? [closed]

What should be dependent and independent variables and Why should they be used?

### Bonferronni adjustment to multivariate confidence interval of GL with interactions

Background I am trying to compute by "hand" (using excel) the confidence interval width at each point for a multivariate glm with interactions. Questions: For the interaction terms, do I make a new ...

### 2 Multiple Correlation Coefficient with three or more independent variables

The formula for the multiple coefficient of correlation of two independent variables ($x_1$ and $x_2$) and an dependent variables ($y$) is this: What is the formula for three ($x_1$, $x_2$, $x_3$) or ...

### 2 Why StackingRegressor doesn't catch the trend?

I just reviewed very good example of fitting StackingRegressor from mlxtend package. ...

### 2 P value of multiple linear regression

2 answers, 353 views r multiple-regression
I have extremely large number of observations (8524152) of soil moisture, precipitation, evapotranspiration, delta precipitation, and delta evapotranspiration. I ran a multiple linear regression model ...

### 1 A little help in confirming an interpretation on an output

How can we interpret the results in the graph below? Does the R command lm() uses Heteroskedasticity-consistent covariance matrices(HCCM) estimators, or HAC estimators for the inference tests? The ...

### 1 meta-analysis of linear regression coefficients

I have the summary results of a linear regression model with 26 covariates which has been fitted to two independent samples (with different sizes). Now I am planning to use the linear regression beta ...

### 2 Choosing Variables to a Multiple Regression Model [closed]

Right now, I'm trying to use some georeferenced data to predict revenue for some stores. My data set has 21 obs (Annual Revenue for 21 stores), but I have 306 variables (Population/pop density, area, ...

### Correct way to determine the (%) contribution of an independent variable to a MLR model

Is the following methodology correct: Fit a multiple linear regression model Obtain the standardized coefficients Sum up the absolute value of all standardized coefficients Divide each individual ...

### 2 Logistic regression - High Correlation between Independent Variables

I am running a Logistic regression on 6 independent variables and running chisquare tests shows high degree of association between 4 independent variables. Most of the topics suggest running first uni-...

### Model for differing aV over time

0 answers, 11 views r multiple-regression model
I hope someone may has some tips for me which Model I should set up for my Research question. Think of the following Design: cognitive tests were conducted at ages 5, 10, 15, 25 (cT) every person ...

### 1 multiple linear regression, confounding, group level predictors

I'm investigating the influence of several independent variables (IVs) (measured on the party,district level and individual level) on individual level campaign behaviour of ordinary candidates (index ...