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

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Regression for correlated variables. (not multicollinearity)

I have a dataset X, and i'm trying to predict the response variables: a, b, c given an instance x. Typically, one might run whatever regression routine on a, b, and c seperately. However, what ...
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2answers
16 views

What is the difference between RSE in training set and test set?

Is the process of calculating Residual Standard Error in Training Set and Test Set same?
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1answer
9 views

Definition of 'Model Diagnostics'

Can anyone help me out with explaining what the term 'model diagnostics' refers to when applied to multiple regression please? In particular, what tests are necessary to check whether your estimated ...
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6 views

Multiple Linear Regression, Permutation and FDR

Suppose I performed standard permutation testing with multiple linear regression. That is, I performed linear regression multiple times after permuting the response variable. I now have the ...
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1answer
82 views

^ symbol in lm() in R

I asked this question in Stack Overflow: http://stackoverflow.com/questions/29710525/symbol-in-r-lm I feel like here would be a better place to get an answer. What exactly does the ^ symbol do to the ...
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1answer
11 views

What is the baseline level in a factor-by-factor interaction?

What is the baseline level for a factor-by-factor interaction term in multiple regression? Consider this example from Fox 2003. In the regression below, these two variables are categorical: ...
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8 views

Body Analysing Scales - the maths? [on hold]

Wondering if anyone has bothered to gather the data and do the maths necessary to determine which of the common: Total body Water / Fat / Lean Mass regression equations are lurking in their ...
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Model diagnostic tests for local linear regression

What are some of the model diagnostic tests which are used/ would be suitable to use for a local linear regression model? Note that this is not the least squares linear model, but rather a special ...
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1answer
47 views

syntax for nls model with breakpoint

So I am trying to fit the model $$Runoff = \begin{cases} \beta_0 + \beta_1Pcp & \text{if $(Ant + Pcp) < Thold$;}\\ \beta_2 + \beta_3Pcp & \text{if $(Ant + Pcp) \geq Thold$;} \end{cases}$$ ...
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multivariate analysis [duplicate]

At bivariate analysis, employment was significantly associated to the outcome. However it was thrown out at the point of determining significant variables (using stepwise method) to assess for ...
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identify influencers - non social netwrok [on hold]

How to identify an influencer, once doen how do I assign probababilities to the other people of being influenced by this influencer? I have a database that I have created segments in based on various ...
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1answer
32 views

How to describe meaning of R squared?

What is the correct interpretation of R squared? How do you typically write the results? Could I say something like Age explained 30% of variation of the car condition index. Please help :)
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1answer
34 views

Why can OLS account for non-linearities even though linearity is assumed?

One standard example when introducing OLS in econometric classes is modelling the log-wage by education and experience. Often, the example models account for experience by not only by the experience ...
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ARCH + GARCH sum to more than 1. Dropping the intercept

I am capturing the daily percentage returns of a stock index with dummy variables. I do this both including and excluding the intercept. I get quite different results. If I keep the intercept (image ...
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Choosing weights for linear regression lm in R for time decay?

I am modeling server performance. Basically load~hits. I want the older hits data to have less influence than newer because overtime different optimization and code have been installed/applied. In R, ...
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18 views

Question about ridge estimator

I have tried to show that ridge estimator is the solution to following problem min $(\beta- \hat{\beta})^t$$X^t X$$(\beta- \hat{\beta})$ subject to $\beta^t \beta =< d^2$ and $\beta$ is a $p$ x 1 ...
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2answers
25 views

Linear regression scaling independent variables

I am trying to do a linear regression. My $y$ variable is typical pretty small approx 0 to 0.3 I have some $x$ variables (regressing them individually on $y$ to start with) though that are very ...
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1answer
33 views

T-test or regression?

I have the following kind of data id age x 1 22 2.1 2 25 2.3 3 50 1.3 where $x$ is some measurement variable. I would like to show ...
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14 views

R - quadprog package for constrained Lasso (penalized) linear regression

What I am doing so far: I am doing a constraint linear regression with R's quadprog package, function solve.QP(). The ...
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1answer
25 views

Predict time series data from another

Here is my problem: I have two times series which are highly correlated. One of my time series have one more data point. I would like to predict the other time series missing data. For example (in ...
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103 views

Multivariate Data

There is a built-in data set USArrests data in R software . ?USArrests We use this ...
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Strong drift in residuals with weighted linear regression

I am regressing two related time series and modeling the residuals as an Ornstein-Uhlenbeck process. I wrote a parameterized weighting function to assign higher weights to more recent values, then ...
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1answer
25 views

Difference between statsmodel OLS and scikit linear regression

I have a question about two different methods from different libraries which seems doing same job. I am trying to make linear regression model. Here is the code which I using statsmodel library with ...
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1answer
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Exploring a two-way interaction in multi-level regression, why do I get significant contrasts when the confidence intervals overlap on the graph?

I'm exploring a significant two-way interaction in a multi-level random-effects regression. The graph (below) appears to show the interaction is driven by differences at low X, and that at high X the ...
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32 views

Is Predicted R-squared a Valid Method for Rejecting Additional Explanatory Variables in a Model?

I'm building a model to understand the important drivers from a set of possible drivers for a time series of data. In my case the possible drivers are other time series. Like most statistical models ...
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Time - series analysis data set should be converted to return or taken its Ln?

I'm studying time series in E-views. And I want to investigate Granger - causality between exports imports and economic growth. So, I'm doing causality and co-integration analysis. I have export, ...
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Recovering original regression coefficients from standardized

Suppose I use Least Squares to estimate coefficients in the standard linear model with design matrix $X$'s columns standardized, so the model is $$ E[y] = X^*\beta^* $$ where $X^*$ is $X$ with columns ...
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R: Formula with multiple Conditions and Categorized Surface Plot [migrated]

I want to make 3D plots for linear Regression Models in R: I wish to display surface of the regression plane of a linear model. I have 2 continuous variables (say AGE, HEIGHT) and 2 factors (SEX, ...
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How to interpret factor by factor interactions?

I'm a bit confused on how one should interpret factor by factor interactions, and what interpretations can be validly extracted. Consider this example from Fox 2003. In the regression below, these ...
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21 views

Regression analysis of Distance Covered by a football player [on hold]

I am supposed to create a regression analysis project to my Econometrics class. The dependent variable would be Distance Covered per game by a player and the indipendent variables would be the ...
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1answer
59 views

R and Regression: How to determine distribution of residuals?

I have residuals from a linear regression model on my data set. I want to find an appropriate distribution of my residuals. Say, I assume my residuals are Skew-T Distributed, how can I find the ...
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2answers
52 views

Linear regression multicollinearity

I run linear regression with Posttest scores as DV and Pretest scores and Group as IVs. Collinearity Statistics Tolerance shows .998 both for Pretest and Group (VIF 1.002). Is this one of the ...
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Different results with each test/ train set

I'm new to machine learning and is facing a very basic problem. I have around 500 labelled data with 8 features. I'm trying to build surrogate models on this data using linear regression. I want to do ...
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How does the presence of factors affect the interpretation of the other coefficients in a regression?

The answer to Interpreting coefficients of an interaction between categorical and continuous variable contains a phrase that seems to have some significant impact on how coefficients are interpreted ...
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How to write down a logistic regression formula with multiple levels of a categorical variable

I dont know how to correctly present a logistic regression model in expressions or formula in a manuscript or a report, especially with a multiple-level categorical variable. For instance, I have a ...
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How to run regression analysis without extracted factors from factor anlaysis?

I used Oblique Rotation in my Factor Analysis to reduce the dimensions and to extract 4 factors. But Since I was using Oblique rotation, the results of Factor Analysis did not contain the extracted ...
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1answer
17 views

Standardize within cohort or standardize within entire sample?

Suppose I'm interested in regressing variable A on variable B. I have two cohorts and want to be sure that there is not an interaction between cohort and variable B, so I include that in the ...
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Regression with percentage change?

As the education rating of a Canadian city decreases by $1\%$, the crime rating will change by ___ (make sure you include the negative sign if warranted) The line of the equation I found to be ...
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Weekly frequency [on hold]

I'm analysing weekly time series data. Years have different numbers of weeks, some 52 and some 53, but by time series assumption it has to be constant frequency. How can I fix frequency problem?
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Linear models comparison

I created two linear models to see if a treatment (switching an instrument) significantly affects the relation between two variables. The variables in the model are the same (Concentration ~ Signal), ...
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1answer
19 views

How to interpret the Durbin-Watson test output in R [on hold]

Just for "train" with linear regression in R I'm doing a Durbin-Watson test over the residuals of a regression (over stock ...
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18 views

Bad regression predictions with probability values

I have to pull through a regression on a set of probabilities (so values between 0 and 1). Those probabilities are related to a binary variable, which I have to forecast exactly. My code basically ...
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Difference between meta-regression and linear regression in Stata?

I'm quite new to Stata, so I have a question about meta regression. I'm performing a metareg with the variable: 'sumvariable' which can have a value of (0-6). I want to see what this variable does to ...
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linear regression and plausibility of forecast

Does there exist any mathematical model where the plausibility for a forecast of the dependent variable by linear regression could be expressed. E.g. in terms of any laboratory parameter measured and ...
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29 views

Very large odds ratio- binary logistic regression

I have obtained a very large odds ratio and standard error for my interaction term after running a binary logistic regression. My study has 4 conditions and 3 dependant variables, however, 1 of the ...
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3answers
34 views

Exploratory data analysis for a dataset with continous and categorical variables

I have a data set which has DV and around 40 IVs. I want to select best variables out of the existing ones. I can use correlation, but it requires only numeric variables. I would like to see relation ...
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35 views

P values of coefficients in rlm robust regression

I am using rlm robust linear regression of MASS package on modified iris data set as follows: ...
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29 views

Categorical variable interpretation in “mixed” regression

I have a linear regression with transformed variables: log(y) = b0 + b1*log(X1) + b2*mid + b3*high where "mid" and "high" are dummies from a 3-level categorical ...
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1answer
61 views

Logistic regression: my main effects lose significance when I add my interaction effects. Why?

I have a dichotomous dependent variable for a 2x3 experiment. There are about 30 observations in each cell, for a total sample size of about 180. Each person was only in one cell. The dependent ...
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2answers
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Z-score in the analysis of data

I am being provided z-scores of dependent and independent variables. I was checking if it can analyzed as such as raw data?