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

learn more… | top users | synonyms (1)

2
votes
1answer
10 views

Methods to compare and analyze two columns in a dataset

I have a large dataset containing many different variables of weather, now I'm interested in comparing two columns with value of temp (call them V1 and V2), where V2 is the actual temp and V1 is the ...
0
votes
0answers
7 views

applying Posterior predictive distribution on the data from which the coefficient of regression were predicted

I am new to linear regression modelling. For the given linear model $Y_{current} = \mu+ \beta X_{current} + \varepsilon \sim N(0|\sigma^2)$ Generally, in regression analysis we estimate, coefficient ...
0
votes
0answers
19 views

Polynomial fit based on the addition of two least squares regressions

I'm wondering if there is a way to retrieve analytically the coefficient for a polynomial fit, based on a least-squares regression coming from two independent sources. Let me explain the context for ...
0
votes
0answers
7 views

log loss and squared loss in shrinkage tuning in R?

My model is logistic regression. Is there a way to tune the parameter lambda of lasso or ridge based on cross-validated log-loss and brier(eg. proper scores?) in any R packages? I'm using glmnet ...
0
votes
0answers
6 views

When to use Group lasso over lasso?

Two cases: When should numerous numerical predictors be grouped? is it just based off some theoretical knowledge on the predictors? When should levels(>2) in a factor be grouped together?
0
votes
0answers
8 views

is idiosyncratic volatility equals to 1-R2 from a regression model?

I am reading an article talking about idiosyncratic volatility obtained from using CAPM: rid = αi + βirmd + eid. rid is the excess return for stock i on day d, and ...
0
votes
0answers
16 views

How to automate linear model in R [on hold]

I have a data wherein for a specific brand weekly promotional information are there along with its sales. Now while running a linear model we generally look at the desired signs of the variable along ...
0
votes
0answers
11 views

Determining multiple linear regression scores

How do you determine (or extract if already given as an output) the X and Y scores from a multiple linear regression model i.e. in the new space (e.g. using typical linear regression packages in R)? ...
0
votes
0answers
4 views

How to deal with continuous variables with NULL values in prediction tasks?

I'm currently working on a machine learning project, trying to predict the expected revenue from a specific user. I have a long list of features that display the date when the user first performed a ...
0
votes
2answers
64 views

How linear regression can be used - explanation for grandmothers

Educational question. Suppose you have to explain linear regression to your granny. She is well educated, she knows even the idea of the hypothesis testing, but before you start to tell her what ...
0
votes
0answers
15 views

Regression ceoff. p-value as a 'summary measure' of 'indication of relative importance'

I have a paper in front of me (peer reviewed, etc.), which states "comparison of the P values for [the covariates] gives a good indication of the relative importance of each [covariate] for ...
0
votes
1answer
17 views

Poisson regression with offset vs logistic regression

I am thinking to use Poisson regression with an offset variable instead of a logistic regression in case where event is rare, since p (probability of success) is very small and n (sample size is ...
0
votes
0answers
11 views

How to deal with interaction between several dummy variables and one continuous variables in one or two regression models?

I want to know the relationship between revenue and cost in several conditions. Dependent variables is REVENUE.REVENUE is a continuous variable from 0~1000+.I have several key independent variables: ...
2
votes
0answers
23 views

Regression with dummies / fixed effects versus Multilevel Model?

In short: I wonder when I would ever want to use a multilevel model as opposed to a linear regression with appropriate structure. In detail: When I look at Wikipedia, I understand that multilevel ...
0
votes
0answers
7 views

Finding the correct model to infill streamflow data gaps

I have 15-minute streamflow observations for a small stream, but the dataset has some gaps in it. I want to fill the gaps with a regression using observations from a nearby stream (and quantify the ...
1
vote
0answers
24 views

Optimize starting parameters for Bayesian Linear Regression?

I'm using PyMC3 in Python 3 and I'm not sure exactly how to optimize my starting parameters. I'm using the regression dataset ...
1
vote
1answer
24 views

Heteroskedasticity Question

I have a model that's affected by Heteroskedasticity: bptest(m1) studentized Breusch-Pagan test data: m1 BP = 65.055, ...
1
vote
1answer
12 views

Regression Using Surveys with Unequal Number of Responses

I am trying to figure out how to properly do regression analysis on a data set from a peer-review survey where individuals in the survey have an unequal number of responses. Below is description of my ...
2
votes
0answers
26 views

Logistic Regression: Should I include a non-significant variable that notably increases the OR of a significant variable?

I am studying the effect of different pollutants on the probability of a genetic mutation. My binary logistic regression models are as follows: Model 1: Dependent variable: genetic mutation (binary ...
3
votes
2answers
66 views

Robust methods and penalized regression

Are penalized regression methods such as ridge or lasso sensitive to outliers? If so, what options are there in regards to robust methods for penalized regressions and are there any packages in R?
2
votes
1answer
17 views

Confidence Interval for Regression Line (simple linear regression)

So I've constructed a confidence interval for my regression line. However, because I have 2500 data points it is a very, very narrow interval (I can barely see it next to the regression line when I ...
0
votes
0answers
8 views

Anova output in R when testing lm() [duplicate]

I am trying to make a simple linear regression to see if my variable "totalssq" has an influence on my variable "hadsa". (my data is "dstatss") Both are quantitative. I made a model with lm() and ...
0
votes
0answers
15 views

Interpreting regression Output for CAPM

I have an interpretation problem. As you can see below there's a linear regression output for the CAPM. I don't know how to interpret the significance level. ExIndex has a very low p-value, but the ...
-1
votes
0answers
22 views

Converting from strings to factors in R [on hold]

I am having a problem converting from strings to factors. This is my code and in it is how I tried to convert from strings to factors. ...
0
votes
0answers
7 views

Why would Conversions and Conversion Rate not correlate strongly?

Do any of you know, or have thoughts about, why website Conversions and Conversion Rate would not give a strongly correlating r-value (pearson)? When analysing some data I'm getting r-values of around ...
0
votes
0answers
13 views

How to analyze technology acceptance model hypothesis with regression analysis in SPSS

I want to ask how to do regression analysis using SPSS with my survey data. My survey data consist of 15 question items which belong to 4 groups: Perceive of usefulness, Perceive of ease of use, ...
2
votes
1answer
34 views

How to prove that $Cov(\hat{\beta},\bar{Y}) = 0 $ using given covarience properties

To quote: It is well known that, if $W_1, ..., W_n, Z_1, ..., Z_m$ are random variables and $a_1, ..., a_n, b_1, ..., b_m$ are constants, then $Cov ( \sum_{i=1}^n a_iW_i, \sum_{j=1}^m b_jZ_j) = ...
0
votes
0answers
20 views

Prediction with a linear simple regression model - out of sample testing

I am validating a model and was analysing the residuals. Although they have mean zero and st. deviation close to zero, when I plot them (q-q plot), they don't seem to follow a normal distribution. Is ...
0
votes
1answer
10 views

Checking linearity assumption and colinearity assumption

Linear regression is equivalent to ANOVA. Do we need to check for linearity and multicolinearity for ANOVA? I have seen that these assumptions are usually omitted for ANOVA but not for linear ...
0
votes
0answers
8 views

Relationship Between Correlations and Contour Plots for OLS

In the paper, "Simultaneous Regression Shrinkage, Variable Selection and Supervised Clustering of Predictors with OSCAR" (Bondell, Reich), the authors state: "As the contours are in terms of $X^TX$ ...
0
votes
0answers
9 views

What explanation can i give for having a negative correlation coefficient but positive regression coefficient? [duplicate]

The first table is the regression results showing negative correlation coefficients for all variables. However in the regression table below, only EXR shows the same association as the correlation. ...
0
votes
0answers
20 views

Using confidence intervals with Simple Linear Regression

So simple linear regression is performed on 3000 data points, and 1000 data points are withheld. How can we use confidence intervals, along with the withheld data points, to assess the predictive ...
0
votes
0answers
9 views

Find a significance difference between two models

I am trying to determine if immigration status is a determinant of risk preferences. To do this, I am using the 2014 Health and Retirement Study data which has approximately ~20,000 participants and ...
0
votes
0answers
14 views

Cross validated loglikelihood?

This is probably a silly question: I was playing around with penalized package and cvl outputs a cross validated loglikelihood and another measure just called loglikelihood which is suppose to be ...
1
vote
1answer
38 views

AICc is picking overly complex models - something stricter?

I'd like to know if there are "stricter" alternatives to automated model selection than AICc / AIC / BIC. We have approximately ten thousand curves, and for each we'd like to find the most ...
0
votes
0answers
20 views

How to plot a vglm/propodds regression in R

Hi I'd like some help plotting the following regression in "r": fit1_usesrp <-vglm(rp ~ is.native + is.male + oh + cjs + age2 + tw ,propodds, data = dummydata ...
0
votes
0answers
13 views

Overfitting: Mean and variance

I have read in a book the next property: Let's consider the following true data generating process: $$y=x_1 \beta_1+...+x_p \beta_p + \epsilon = x_{true}' \beta + \epsilon$$ where $E(\epsilon)=0$, ...
0
votes
0answers
7 views

Regression Analysis - Individual vs. Aggregated Team data

I have a set individuals (let's say ID_No 1 through 50) and a set of metrics that pertain to these individuals: things like age, SAT reading score, SAT math score, a motivation index metric, etc. ...
0
votes
1answer
70 views

More features than data points in linear regression

In a dataset with more features (e.g. 120) than data points (e.g. 60) what are the techniques commonly used to select the best features to apply linear regression? Obviously there is an efficiency ...
0
votes
2answers
33 views

How to summarize R-squared of several regressions, one per subject

I will explain my question, I have made a study and I have 10 regression (one for each subject). I have a significance for each regression, but in some subjects the value of R-squared is 0.5 and in ...
0
votes
0answers
9 views

Moderation in regression - what to enter

I am doing research into the effect of an IV on a DV. Additionally I have identified several possible moderators (3) which all consist of 3 variables. E.g. possible moderator job demands consist of ...
1
vote
0answers
35 views

Why use group lasso instead of lasso?

I have read the that the group lasso is used for variable selection and sparsity in a group of variables. I want to know the intuition behind this claim. Why is group lasso preferred to lasso? Why ...
0
votes
1answer
23 views

the graph of log(-log) for Cox model on survival analysis

I'm studying Cox Regression model on Survival Analysis. While testing validity of Proportional Hazard model, I will use log(-log) graph method in SPSS. First of all, I mention which procedure I'm ...
0
votes
0answers
15 views

How to write a regression equation with an unknown structural break point? [on hold]

Using STATA's estat sbsingle function post a multiple regression I have found a statistically significant structural break. However I am struggling to express this in a mathematical/statistical ...
0
votes
0answers
14 views

Logistic regression in R when data when variable is a number of observations in a set of categories, not indicator (dummy variable) [on hold]

I have data in the form, let's say, factor1 | factor2 | number of observations in given levels of fctr1, fctr1. How do I perform logistic regression?
0
votes
0answers
9 views

What approach statistical approach for multiple observations but different treatment/control participants?

I have multiple observations over a period of time. Each observation has a different treatment group and a different control group. I am interested in understanding whether behavior was different at ...
0
votes
0answers
10 views

Understanding vglm/propodds regression output in R

I was wondering if I could have some help analyzing the output from a regression. Some background on what I'm trying to find/my data: I am trying to determine if immigration status is a determinant ...
0
votes
2answers
25 views

Which of the 3 cases should my data matrix belong to ideally?

I found this question, and while useful, I wanted to ask something more spcific: I am trying to get a good handle/intuition for the two types of data dimensionalities (number of data samples, and the ...
0
votes
0answers
19 views

How to use a regression lm function used for prediction [migrated]

I apply a linear regression over a data set: ...
0
votes
0answers
14 views

How we can find trend of time series and turning points?

I want something like this in a time series: Currently I'm using some linear interpolation to find trend and turning points. What other methods can I use to find these turning points in a time ...