Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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Interaction between 2 quadratic variables

If I have a regression y ~ x1^2 + x1 + x2^2 + x2 + bias, and I want to include interaction between the two quadratic variables, do I make the new regression y ~ x1^2 + x1 + x2^2 + x2 + x1^2*x2^2 + x1^...
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8 views

ARMAX or Dynamic Regression | regression of multiple timeseries

I have the following time series dataset (dependent | independent) : Sales | Income,Inflation, Interest Rates etc All of this is dynamic data pertaining to each ...
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14 views

How to calculate adjusted Y after controlling on X?

This seems should be a common question, but I couldn't find the answer after search around. Let's say we want to calculate student adjusted math test score after controlling on family income. And ...
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10 views

How do I manually calculate linear multiple regression coefficients? [duplicate]

I am working on an assignment in which I need to manually calculate the coefficients in a multiple linear regression model with 6 predictor variables. I also need to demonstrate my working. I found ...
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11 views

Significant interaction but simple slopes non-significant [on hold]

I have looked at the boards and have yet to find a clear answer to this question. What does it mean when there is a significant interaction but the simple slopes are non-significant besides that they ...
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Linear Regression and Almost Sure Convergence

Consider a linear regression model, wherein: $$ y_{i}=x_{i}\beta+\epsilon_{i} $$ where notation is standard and $x$ is a scalar. Let us further impose the following restriction: $$ \epsilon_{i}|x_{i}\...
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25 views

Regression + Time series

I have time series data about sales/day, but i also want to include other data (static/dynamic) to forecast the time series. Is it possible to combine ARIMA model and regression models to achieve the ...
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1answer
43 views

Running many multiple regressions at once in R

I want to run time series regressions (Fama-French three factor with my new factor). I have following tables. ...
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11 views

Number of symptoms and genotype - what is the correct type of regression to use?

I apologise if I do not use the correct terms when describing my problem but hopefully you can help me. I have a data set with around 430 participants. They have given information on the number of ...
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14 views

The Appropriate p (number of predictors)/n (number of observations) Ratio in Tree-based Methods

I am dealing with a dataset in which there are 493 observations spanned over 30 predictors. My intention is to fit a model to make accurate predictions. It seems to me that the ratio $\frac{n}{p}$ ...
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2answers
21 views

How to pick the students with the greatest improvement based on ZScore?

I work for a school. I have a pool of data from past examination results. For example, John did five tests so far and his marks look like this: 60, 70, 55, 80, 60. I then convert them to ZScore. They ...
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Regression to elucidate for specific effect of a treatment

Regression has commonly been used to adjust for baseline characteristics between groups in clinical trials. If a drug is known to cause effects (improvement) on A & B, and I am interested to ...
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Training instances importance in Random Forest?

Is it possible to determine the importance of the training examples in Random Forests, analogously to what's done with predictors? Basically the idea would be to find important samples in the data, ...
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21 views

Too many models to choose from

I'm trying to find a good evaluation function to approximate the score of a position of the game Reversi. That is the score of mutually perfect play. A position of Reversi has 64 fields, with each one ...
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2answers
39 views

How to reduce the number of labels in regression

I'm working in a regression problem, related to bio-signals, where my labels are integer numbers between 0 and 10. I've tried a couple of regression algorithms already, mainly linear regression. Edit:...
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13 views

A Question on Interactions in STATA [on hold]

I am trying to replicate one of Wooldridge examples to learn a bit. It is about interacting the dummy variable (black) with a continuous variable (percblck). Here is the code that I have written: <...
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9 views

Step by step guide for GRS test in R? [on hold]

I'm new to R. I have basic knowledge in R. I'm testing a factor model. I have to use GRS test. But not sure how to do it. Please help me. I have found this recipe for GRS online. http://faculty....
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17 views

Neural Networks for simple Regression: Y=X^2

All I'm trying to do is make a simple neural network to learn $y=x^2$ (Just as a toy example with x ranging over the integers between -100 and 100) with Tensorflow, but I'm having a surprising amount ...
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9 views

Multiple R Using Multiple Predictors vs. r of Composite of those predictors

Can someone please explain the relationship between a Multiple R using multiple predictors in a multiple regression vs. a simple correlation between a composite scale (comprised of the same predictors)...
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11 views

Partitioning variance among three scales

I'm trying to create a diagram depicting proportion of shared and unshared variance among three scales. While brainstorming how to do so, I came up with two methods: 1.) Method 1 -- Regression ...
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31 views

Quantitatively analyzing relationships between multinomial and multiple binomial variables

I’m analyzing crowdsourced Twitter data, where workers labeled tweets. Within my dataset (N=2,400), I have one IV (call it ‘ds’) with 2 levels that differentiates which dataset the workers labeled. I ...
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19 views

Bayesian Variable Selection with NMIG

I have a Bayesian linear model like this: $Y_i = X_i*\beta + \epsilon_i$ . Just for completion: ($\epsilon_i \sim N(0,\sigma^2)$ $\beta \sim N_p(b_0,B_0)$, $\sigma^2 \sim Inv-Gamma (a,b)$) I would ...
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linear regression and residual [on hold]

A simple linear regression analysis resulted in b0 = 40 and b1 = 3. If one of the observations in your data set has a value of Y=14 and X=8, what is the residual for this observation?
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1answer
20 views

Which glm family to use for ordinal DV?

I'm trying to test whether duration of time spent on the Internet (ratio scale) can predict behavioural problems (ordinal, with scores ranging from 0-10). I just wanted to double check that an ordinal ...
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22 views

Regression or time series model to predict trend

DATA I have the following data at hand: data about internet usage, per hour, per user, per part of the day (morning, afternoon, evening); the category of websites visited and their duration; ...
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46 views

Assessing feature importance without random forests

What ways are there to assess variable (feature, covariate) importance in regression models, except for using random forests? (For instance, using OLS regression, Bayesian parametric regression, etc.?...
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What is tolerance technique that use to deal missing data?

Current administrations of processing missing data can be approximately divided into three categories: tolerance, ignoring and imputation-based procedures. i- Missing data ignorance often refers to ...
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Does selection of predicted vs. reference class matter in hierarchical multinomial regression?

A simplified example: There are three classes: $1$, $2$ and $3$. They have a natural order, i.e. $1<2<3$. I have a different number of observations of the classes, e.g. $1$ has been observed ...
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1answer
22 views

Why does the Arima() method in the forecast package in R not calculate standard errors for coefficients passed to 'fixed'?

In the Arima() method, in the forecast package in R, I can provide a vector of parameters to the ...
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5 views

Matlab nn tool data interpretaion regression equation [on hold]

How to get predicted data and regression equations in nn tool using matlab software i need the set of commands to get the same
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15 views

Are my regression lines from the same population? [duplicate]

I have two sets of data looking at weight change over time. Subjects within each data sets have weights at multiple time points. The first is a small set of data I used to determine an equation to ...
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1answer
18 views

Filtering data depending upon conditions in 8-9 columns and then applying regression on the filtered data [on hold]

I am new to R programming and need to analyse a very large set of data, I have around 660 rows to be analysed and 9-10 columns.For each row I have values in the columns like (0,1,2,3,4,5) I need to ...
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27 views

Hand computation for plm package in R (twoways model) for predicted values [on hold]

I have one question on the plm package. I try to compute predicted value in the case of a twoways (effect = "twoways") model. ...
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2answers
34 views

Logistic regression with only categorical predictors

So I started off with a model which included both continuous and categorical predictor variables. But now I wanted to drop the only continuous variable (distance to shore), because to my opinion it ...
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18 views

Intuition: Why do I have to worry about errors-in-variables?

I've read that (ordinary) linear regression assumes that there are measurement errors in the dependent variable, but no measurement error in the independent variables -- and if I have measurement ...
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1answer
40 views

Interpreting R regression output with multiple interaction variables

Context I am exploring how different factors in targeting affect subjects' self-reported likeliness to purchase a product. Likeliness to purchase was measured on a four point scale: "Very unlikely", "...
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2answers
58 views

What's wrong to fit periodic data with polynomials?

Suppose we have toy daily temperate data and we want to fit a model. A reasonable thing to do is fitting a periodic model with Fourier basis $$ f(x)=\beta_0+\beta_1 \cos(2\pi x/24)+\beta_2 \sin(2\...
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Correlation between residuals of two different relations

I have two relations, A=f(B) and C=f(B). They both are different physical quantities depending on the same variable (let's say pressure=A density=B, temperature=C). I fit both relations to my data. ...
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3answers
349 views

Moderated regression: Why do we calculate a *product* term between the predictors?

Moderated regression analyses are often used in social sciences to assess the interaction between two or more predictors/covariates. Typically, with two predictor variables, the following model is ...
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2answers
34 views

How to apply classifiers from k-folding to data not used in the k-folding?

When I am using k-folding to split my labelled data (labelled as signal or background) and train k classifiers on it, I believe I am not allowed to assume that the distributions of the classifier ...
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1answer
49 views

Estimating risk in linear regression analysis

I am relative new in regression analysis. I would like to know, if there is a way in regression analyis to estimate the risk or calculate the risk for future values? An example: We want to predict ...
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31 views

The use of PCA index as a dependent variable

My question is a follow up one to the use of PCA as a dependent variable which was posed by Singh and answered by Sympa on May 22, 2016: Principal Components for dependent variable in a regression. ...
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76 views

Can I use PCA (or should I use regression) for testing the effect of multiple variables on one dependent variable?

I have 2000 soil property measures and 14 different variables like rainfall, temperature, slope, etc. I want to check the effect of those 14 variables on soil property measures, including which ...
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1answer
26 views

Regression model for pre-post single group design

I am analysing cross-section data from two time points, i.e. before and after an intervention and I am particularly interested in the causal effect of the intervention. The outcome of interest ($Y$) ...
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14 views

Regression coefficients that are regressed on other predictors

I would like to have individual specific regression coefficients, which means the coefficients are also modeled by some predictors. The model in my mind may be like this: $$y_i=\alpha_i z_i+\epsilon_i$...
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13 views

Using differences or ratios in regression

Is it always wrong to use ratios in linear regression? For example, If I am trying to fit a linear model and I have a predictor given by: average age of team A / average age of team B should i ...
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20 views

Simulate different types of outliers (with R) in a linear regression?

I'm trying to simulate a regression model with outliers to implement and understand more deeply the robust regression. I tried using a mixture between normal errors and uniforms.But as you can see, ...
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Trouble fitting contrained regression in R software [on hold]

I'm trying to run a constrained regression in R. My model is (there is no intercept): $$ Y = \pi_1 X_1 + \pi_2 X_2 + \pi_3 X_3 + \pi_4 X_4 + \pi_5 X_5 + \pi_6 X_6 + \varepsilon, $$ subject to the ...
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Method to predict action based on previous sequence of actions

Given $n-1$ sequences of actions [$k_{i1}$...$k_{in}$] as training/example I want to be able to predict $k_{nn}$ in the sequence [$k_{n1}$...$k_{n(n-1)}$] where $k_{nn}$ would be the most likely ...
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1answer
16 views

Regression with linear transformed matrix

Intuitively (formal explanation is also welcomed), what would happen if we use a linear transformed matrix in regression? $\mathbf{XZ}$ instead of $\mathbf{X}$ in $Y = \mathbf{X}\beta +\varepsilon$. I ...