This tag is a signal that the question focuses on a problem particular to multivariate analysis, such as multiple correlations or interactions.
0
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0answers
31 views
Why is the condition of my design matrix so bad? [closed]
I've got a 4000 x (numParameters + 1) design matrix for this regression I'm doing... but no matter which parameters I choose, even if I make it a 4000 x 2 matrix with just the intercept and one of my ...
0
votes
1answer
40 views
Normalized root mean squared error (NRMSE) vs root mean squared error (RMSE)
The response values in my data set (100 data points) are all positive integers (should not be either negative or zero values). I have developed two statistical models: Linear Regression (LR) and K ...
1
vote
1answer
40 views
Which bootstrapped regression model should I choose?
I have a binary logistic regression model with a DV (disease: yes/no) and 5 predictors (demographics [age, gender, tobacco smoking (yes/no)], a medical index (ordinal) and one random treatment ...
0
votes
1answer
20 views
Search for interactions using carets rfe function
it is straight forward to search for purely additive models using the rfe function in caret. Is it possible to include all interactions as part of the search?
In the train method, we can simply say ...
0
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0answers
25 views
Remove terms with NA coefficients from lm model with interactions [migrated]
I'm training a model using lm with interactions by
fit <- lm(Y ~ .^2, data)
Some of the interaction terms have "NA" as their coefficient, indicating I suppose ...
1
vote
0answers
31 views
GRM or mixed effect models
I need your help.
In experiment I have measured the grow of one plant on 40 locations. At one location different number of plants were measured, but always the same species. The distribution of ...
4
votes
1answer
57 views
Linear relationship between explanatory variables in mutliple regression
I was reading the multiple regression chapter of Data Analysis and Graphics Using R: An Example-Based Approach and was a bit confused to find out that it recommends checking for linear relationships ...
1
vote
2answers
61 views
Dummy variables in multiple regression, why use an intercept?
When performing a multiple regression with dummy variables, is it really necessary to include an intercept term in the design matrix?
By dummy variables, I mean indicator variables; a one in the ...
1
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0answers
20 views
MR with dummy variables
I need to calculate MR but my data consists of many dummy variables. I had a question in my survey that asked for the budget/month. But instead of giving the option to fill in a value, I offered ...
1
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2answers
49 views
multiple regression and multiple comparisons
Say I fit a multiple regression of p explanatory variables. The t-test will allow me to check if any single one of those is significant ($H_0: \beta_i = 0$). I can do a partial F-test to check if some ...
2
votes
1answer
41 views
Why does latent variable modelling in regression tend to push R Squared up?
Hypothetically, say I have I have three manifest variables measuring anxiety and three manifest variables (items) measuring stress. Then I want to use both to predict scores on depression, which I'm ...
1
vote
1answer
46 views
Simulating multiple linear regression
I would like to simulate a multiple linear regression model using R.
If I have the skewness and kurtosis for the residuals, how can I do that?
3
votes
1answer
101 views
Dummy coding for contrasts: 0,1 vs. 1,-1
I'm seeking your help in understanding the difference between two different contrasts for dichotomous variables.
On this page:
http://www.psychstat.missouristate.edu/multibook/mlt08.htm
under ...
0
votes
0answers
50 views
R linear model summaries, why is one model “better” than the other?
I am attempting to get my head around the summaries of linear models given within R. In other words i am trying to identify when the summary of a model is good or bad. Consider the following two ...
1
vote
1answer
46 views
Multiple Linear Regression Simulation
I'm new to the R language. I would like to know how to simulate from a multiple linear regression model that fulfills all four assumptions of the regression.
1
vote
0answers
44 views
can ordinal variables be used as predictor for linear multiple regression analysis?
Part of my thesis tries to investigate the extent to which students "test Score" on the topic of electrical circuits in physic can be predicted from how they find the topic to be "interesting" ,Their ...
0
votes
1answer
83 views
How to handle Regression data thats not linear
I'm new to stats and am using Python 2.7 to fit a regression model (Random Forest). When I plot the percentile plot of the prices before and after a log ...
1
vote
2answers
75 views
Help with Anova of categorical and continuous variable in R and SPSS output
I am having some trouble running an Anova on categorical variables in R and matching SPSS output. What I need to do is run an anova on the dataset below (its a made up data set). But, I need to know ...
1
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0answers
54 views
Is it a true main effect if it is significant only when interaction is included?
There is a question What if interaction wipes out my direct effects in regression?. An answer was given that the true main effects are in the model without the interaction.
I have the opposite ...
0
votes
1answer
44 views
Is there a statistical model for modelling variables that are measured in varying amounts and in different time points per individual?
I have been trying to model a dataset of variables where each individual is measured a different number of times, and on different point in time. Most of my variables are count, but some are not (the ...
2
votes
1answer
44 views
Effect of corrections for multiple testing on sensitivity and specificity
Let's imagine we have one variable (factor.to.explain) that we want to explain by 10 other variables using 10 linear model (no interactions computed). We should correct for multiple testing. It is ...
0
votes
0answers
53 views
Statistical tests on the revenue data of a small business
I have daily revenue data from a small business with 6 locations. The business sells food products that range from roughly \$2.00 to \$9.00, mainly to professionals. They do over a million dollars a ...
3
votes
2answers
49 views
Compare fit of ordinal to linear model
I´m doing multivariate modeling on a dataset where the dependent variable is ordinal-values running from 0-11. So far I´ve done general linear models and it runs alright. However, I´d also like to run ...
1
vote
0answers
35 views
How do I set up a multivariate hierarchical multiple linear regression in R?
I have two continuous DVs (measurements taken on individual fish), one continuous individual level IV (fish's size), and two site-level IVs (PC1 and PC4). Sites are either take or no take. There are ...
0
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0answers
37 views
Multiple Regression questions (restricted regression, dummy variables)
Q1.
Model 1: $Y=X_1\beta_1+\varepsilon$
Model 2: $Y=X_1\beta_1+X_2\beta_2+\varepsilon$
(a) Suppose that Model 1 is true. If we estimates OLS estimator $b_1$ for $\beta_1$ in Model 2, what will ...
0
votes
0answers
10 views
Model with quantitative and qualitative explanatory variables [duplicate]
I have a model with average financial literacy score as the dependent variable and race, gender, and level of education as independent/explanatory variables. Race and gender are dummy variables but ...
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0answers
42 views
Statistics and Data Analysis for Small Businesses [closed]
I am currently a forth year mathematics and economics student. Before this I practiced graphic design. To help pay for school I have continued doing design for a small business in my home city. It is ...
0
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0answers
22 views
Modelling a skewed, 10-point Satisfaction variable
I am trying to replicate and hopefully improve on an analysis done in a study to find determinants of patient satisfaction after shoulder surgery. Satisfaction is heavily skewed (with over 60% of ...
-1
votes
0answers
44 views
How to interpret the results of stepwise multiple regression with multiple subscales in for one measure
My hypotheses for were based on the stepwise regression in which the predictors were constructs measured by four separate measures. Three of the measures have subscales. Since each subscale is put ...
1
vote
1answer
44 views
How to choose interactions to test when there are many predictors?
If I have many covariates $X_1, X_2, ... ,X_{15}$ in a linear regression model, how do I determine which two-way interactions to include? Obviously there would be too many potential models to do a ...
0
votes
1answer
137 views
Can you run a multiple regression where variables use different Likert scales?
I have 8 predictor variables and 1 criterion variable, all variables are measured by 9 different constructs, some are 0-4 Likert scales, some are 1-5 Likert scales, can I use their mean scores and ...
0
votes
0answers
39 views
Pre to Post Repeated measures for categorical dependent variable and more than one independent variables both continues and catgorical
I am doing Prenatal (before delivery) and Postnatal (after delivery) depression assessment (2 time points).
Dependent variable is Depressed/Non depressed mother on a measure of depression.
When as ...
0
votes
0answers
19 views
Mlogit crashes when testing CSV File [migrated]
I am new to this forum and to R so please bear with me. I will try to make my post as detailed as possible!
The R I am using is version 2.9.2 on mac 10.6.8.
I am currently running a mlogit model on ...
0
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0answers
21 views
2
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1answer
30 views
In multinomial logistic regression, can I compare the categories that are not the reference category with each other?
I am conducting multinomial log. regression, my DV has three categories, therefore my output gives me the comparison between the reference category and the other two. I would also like to compare ...
1
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2answers
49 views
One predictor is a linear combination of another
If I try and fit the linear regression
lm(y~V1+V3,data=x)
with data:
...
1
vote
0answers
20 views
Hierachical Predictors in a Regression
Note: Mainly this question pertains to predictions from a model.
If the unit of analysis of a regression (or any predictive model really) is the individual retail store and these stores are organized ...
0
votes
0answers
39 views
How to control intercept of only one IV-DV relationship in multiple linear regression
If I have a relationship between three variables (survivorship (outcome), time and dose (continuous) with interaction) how can I control the intercept for time but not dose in MLR? The reasoning for ...
2
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0answers
58 views
Can we find bounds on R-squared?
We know that as the number of independent variables increases, the coefficient of determination $R^2$ will increase but the adjusted $R^2$ may or may not increase. In the following question for the ...
2
votes
1answer
53 views
Confusion related to data normalization
I am trying to learn a linear regression model. However, I have some confusion related to the normalization of the data. I have normalized the features/predictors to zero mean and unit variance. Do I ...
0
votes
0answers
31 views
Analyzing reflected and transformed variables
I want to perform multiple linear regression on my variables; since my dependent variable was negatively skewed, I reflected it and then I log transformed it.
My independent variables was positively ...
3
votes
2answers
142 views
Getting rid of a huge categorical factor in multiple regression
I have a large regression problem with a lot of cases, but relatively few independent variables. One of them is a categorical factor with thousands of levels. Robust regression runs forever. In some ...
5
votes
3answers
152 views
Explanation of minimum observations for multiple regression
I feel like every question I've asked on CrossValidated has lead back to looking at the number of observations I have per variable. I understand that there are many rules of thumb out there depending ...
2
votes
1answer
73 views
Power of a Multiple Linear Regression
I have a set of models that are the result of a multiple linear regression. I would like to calculate the power for each of these models. I found this tutorial on calculating the power using G*Power. ...
3
votes
0answers
65 views
How to do a multiple regression with ARIMA using R?
I am analyzing some tree physiology data (transpiration) in relation to a number of environmental variables (many of which are predictors such as temperature, PAR and vapour pressure deficit).
I ...
0
votes
0answers
26 views
Two IVs (schools) and 3 IVs (grade levels in each) where there are 2 DVs (math and reading scores)
Is MANOVA the correct test? I am looking at 3 grade levels in each of the two middle schools. I want to compare the standardized scores (reading and math) of students in each grade level to the same ...
3
votes
1answer
92 views
What is an unbiased estimate of population R-square?
I am interested in getting an unbiased estimate of $R^2$ in a multiple linear regression.
On reflection, I can think of two different values that an unbiased estimate of $R^2$ might be trying to ...
4
votes
0answers
53 views
Hierarchical regression using residuals
Edit: Perhaps my first asking (see below) was a little too ambitious. The crux of the question is this: in a linear regression setting, is there anything statistically invalid about regressing the ...
0
votes
1answer
127 views
R2 of validation sample
After removing 25% (21 observations) of the sample as a holdout, model selection on the original 75% of the a sample led to a six variable multiple linear regression with R2 of 54%.
A simple ...
1
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0answers
51 views
Forward Stepwise selection
I am assuming the following model:
$Y = \beta X + \epsilon$
Here both $X$ and $Y$ are matrices. I fit the least squares model without any regularization and get the matrix $\beta$. I would like to ...
