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

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When to include or reject interaction term in two variable linear regression

I am studying a treatment that degrades device quality and performed an independent sample test on two batches that had different initial quality. I analyzed the data with a two variable linear ...
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9 views

Using nlsLM() for importance sampling for pricing european optoins

I am trying to implement a method for finding an optimal drift in pricing European options with importance sampling using this article. The article in pages 489-490 suggests to use Levenberg-...
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7 views

Combining Fixed Effects and Random Effects Confidence Intervals, Is this Possible?

I estimated a random slope,random intercept model and have estimates of the fixed-effects $\beta_i$ and the random effects $b_i$. I also have their associated standard errors $SE_{\beta_i}$ and $SE_{...
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18 views

How to ascribe and defend statistical significance in linear regression. P-value interpretation and alternatives

I am studying a treatment that degrades device quality and performed an independent sample test on two batches that had different initial quality. I analyzed the data with a two variable linear ...
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1answer
29 views

How to generate heteroskedastic data for linear regression analysis given Y

I have at m different points on a surface representing an organ n measures of a organ property for n subjects (such as wall thickness). These values have been stored in a matrix Y with m columns and ...
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22 views

Am I introducing bias by assuming birthdate is middle of month?

I have a dataset containing dichotomous disease measures as well as some continuous anthropometric measures on a cohort of patients, and includes their month and year of birth as well as the exact ...
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8 views

What if two dummy levels does not have constant variance

I am trying to use a binary dummy variables in my multiple linear regression. I have tested the identical slope assumption and it is confirmed. However, I did a side by side boxplot of the two levels ...
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1answer
23 views

Creating a Regression to see how weather can explain sales development

In June, a sales representative explained that the weather in Cologne (Germany) has been very rainy and this is causing sales to drop. Granted, less people go shopping when weather is bad. However, I ...
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1answer
26 views

Negative binomial regression in R allowing for correlation between dispersion & regression coefficients

In negative binomial regression, the MLE of the dispersion parameter is asymptotically uncorrelated with the MLEs of the regression coefficients (http://pointer.esalq.usp.br/departamentos/lce/arquivos/...
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19 views

How to interpret odds ratio in case of less then 1?

How to interpret the odds ratio when it is less than 1? is that ratio needed to be inverted? and if yes, then how to interpret it? can you plzz explain it through an example.
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1answer
24 views

How to calculate the confidence interval of the x-intercept in a linear regression?

Since standard error of a linear regression is usually given for the response variable, I'm wondering how to obtain confidence intervals in the other direction - e.g. for an x-intercept. I'm able to ...
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11 views

How to check each kernel output from a compostie kernel in the Gaussian Process Regression? [on hold]

In the Gaussian Process Regression, the right choice of kernel method (covariance function) is very important because it measures the distance/relation between the current data and future data. I am ...
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38 views

Confused about logistic regression equality

Problem: Prove that: \begin{align} \Delta E(in) &= -\frac{1}{N} \sum_{n=1}^N \frac{y_n x_n}{1 + e^{(y_n w^t x_n)}} \\[10pt] &=\frac{1}{N} * \sum_{n=1}^N - y_n x_n \theta (-y_n w^T ...
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11 views

Hard question - Trying to predict one dependent, continuous variable in 2 conditions, both with different correlations, how do I proceed?

I'm trying to explain the variance experienced with cybersickness, roughly put a type of motion sickness experienced inside of Virtual Reality (more specifically, I put participants in a virtual ...
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8 views

How to calculate regression coefficients in terms of original variables when I already have regression coefficients in terms of PCs? [duplicate]

While doing principal component regression I take the input data, standardize it, calculate PCA, and use the score matrix to solve the equation Y=score*B where Y is my mean-centered known output and B ...
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21 views

Feature Selection with Categorical Variables: Multicollinearity and Statistical Significance

Building a logistic regression model with three categorical features and one continuous. For simplicity, let's say I have the following features and variables: ...
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4answers
289 views

Logistic Regression: Does my model selection process make sense?

This is kind of a broad question and so I am okay with broad or general answers. In fact, each of these could be their own individual questions, but I think it makes sense to ask them all. Even if you ...
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7 views

should i be treating variable for non-linearity for neural network model?

We usually treat the variables for regression analysis for any non-linearity. Now since we fit a non-linear function in NNet, should we be treating the variables for linearity before feeding into ...
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Circularity in Linear Regression: Independent variable used as dependent in the same model

I have a dataset with at Customer-Date level. I want to fit a line on the data estimating spend of a customer on a certain date. One of the covariates I am using in the model is historical sales of ...
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2answers
28 views

Assigning a transfer value of a Football player given performance scores

I just recently landed my dream internship at a football statistics company and I am eager to impress. I have an excel spreadsheet of every player in the major leagues along with the minutes they ...
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32 views

How to interpret the coefficients of logistic regression?

I want to understand the interpretation of logistic regression coefficients in terms of an increase in probability of dependent variable being 1. I tested a logistic regression model in R and got ...
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15 views

Machine Learning: Non-Linear Regression over dataset with very similar predictors and very different targets

I have a time-series dataset collected by a group of biologists counting the abundance of a particular animal species in an area. I later enriched this dataset with weather variables (e.g. temperature,...
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7 views

Multilevel mediation with dichotomous outcomes but continuous mediator

I want to do a mediation analysis in R on multilevel data where the treatment and mediator are group-level variables while the outcome is recorded at the individual level. The documentation ...
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19 views

Machine Learning: How to solve “class imbalance” in Regression Algorithms?

I have a time-series dataset collected by a group of biologists counting the abundance of a particular animal species in an area. I later enriched this dataset with weather variables (e.g. temperature,...
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11 views

How to apply ordinal logistic regression in R using ORM function. how to derive values & predict the category?

The above predicted values (in three rows) are based on the training data set. Is it possible to predict the ordered category with values similar. Ex: if the values for a dependent variable Y , which "...
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How to deal with hierarchal / nested data in machine learning

I'll explain my problem with an example. Suppose you want to predict the income of an individual given some attributes: {Age, Gender, Country, Region, City}. You have a training dataset like so <...
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1answer
44 views

Linear “self” regression, terminology and references?

Suppose that $X_i, i=1,\ldots,n$ are some random variables. I'd like to do multiple linear regression to learn to predict any of these variables from the others. My model for the reconstructed ...
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1answer
20 views

What is an acceptable R squared range for cross sectional data linear regressions?

May I know an acceptable R squared range for a cross sectional data analysis using linear regression? I think the requirement for this is lower than time series or panel data but would like to know ...
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22 views

Observation dependency in logistic regression to learn relevance of search results

I want to predict the most relevant item from a set of search results resulting from a query. Moreover, these items are places; the query is at a lat/long and time; and the search results are ...
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34 views

How to deal with categorical variables in regression [on hold]

I have 3 levels of categorical variables for different programs. I have run a regression model on them in R with the following modifications: ...
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1answer
18 views

How do I know if a model with a subset of the features of another model has lowest training/test error?

I'm doing the Machine Learning specialization from the University of Washington on Coursera, and I have to answer some questions in a quiz from the Regression course. They ask which model would have ...
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1answer
17 views

how the interaction between one binary variable with several binary variables modeled in logistic?

I want to assess the interaction among genotype (coded as 0 and 1) and dietary intake {(fat intake ‎‎(coded as 0 and 1), carbohydrate intake (coded as 0 and 1 and also energy intake (coded as 0 and 1)}...
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Restaurant Transaction Predictions

I'm new with R and have an intermediate background in stats. I'm developing a model that predicts the hourly transactions that a restaurant has. I work for a fast food chain in Latin America (we have ...
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16 views

Do I standardize the response value as well? [duplicate]

In linear regression when my variables have a different scale do I have to standardise only the independent variables or the response as well?
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4answers
81 views

Dummy coding vs. continuous variable in regression analysis

I am doing a regression analysis in R, in which I examine the contribution of each car attribute to its price. Some variables can be coded as a dummy variable, or as a continuous variable. For ...
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18 views

splitting and subset of data in R [on hold]

I have just used sample.split to split my data as follows spl = sample.split(name$money, SplitRatio = 0.7) Then I get stuck ...
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1answer
39 views

Two age variables in regression

I am performing an hierarchical regression. One of the binary factor variables is if someone is 65 or older (1) or if they are younger than 65 (0). However, I am also applying stratification for age (...
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13 views

Why is my semivariance so high?

I am using variograms checking for spatial autocorrelation in a resiudal pattern produced by a GLMM-NB. In theory, the semivariance should be bounded between 0 and 1 (that´s what I think at least as I ...
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11 views

Cross validation for obtaining maximum median SRC Vaue

My dataset is comprised of 5 types of image's sets along with their distortions scores (DMOS) .Let us call the types as Type1,...
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0answers
10 views

Model ratio in a one-way repeated measures ANOVA in R?

I've got a dataset with two measures in a group of people, before (pre) and after (post) an intervention. Second measure is always greater than first one. My assumption is that the initial value ...
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32 views

Why regression output is omitted in Stata?

I am a bit confused of why I get omitted output in my regression results when I know for the fact that all of those dummy combinations are alive and well in my data set: ...
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6 views

Combine various regression equations of different datasets into One universal regression equation

I am trying to build a regression equation for stocks using various inputs like earnings, price movement, etc. The problem is I will get 100 equations if I try to do it for 100 stocks. How can I ...
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10 views

Regression Table for College GPA [on hold]

Table 1 College GPA for Associate Degree Graduates at a college OLS Regression Coefficients. N=608 Independent Variables Model1 Model 2 Model 3 Model 4 HS GPA 0.204** 0....
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1answer
34 views

How confident can you be of prediction accuracy, even in the case of a causal relationship?

If we use the example of the correlation between frequency of cricket chirps and temperature, where there is a causal relationship between temperature and crickets' chirping rates; it seems to me we ...
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32 views

Data classification and regression in R [on hold]

My question is about finding the relationship between speed of a vehicle and its emission. I think, based on the nature of this problem, there is not a constant relationship between the speed of a ...
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4answers
80 views

How can I identify and remove outliers in R

I am performing regression analysis on prices of product that we have purchased, based on size and other attributes. However there are often buys in odd circumstances which factor into the price, ...
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1answer
14 views

Heteroscedascity and sample size

Can a small sample be cause of heteroscedascity? My guess is that it doesn't depends only on sample size, but also on sample bias or measurement error.
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23 views

I want to perform a regression analysis on a Hospital Charge Data Analysis [on hold]

I have a dataset from the following website: https://www.data.gov/health/ which I am using in my final project. I want to perform a regression analysis. My attributes are DRG(diagnosis related drug), ...
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Regression Analysis of Stratified Samples

What is happening in standard survey libraries in statistical software when "strata" are declared in e.g. regression analysis? Are strata typically treated as fixed effects? More broadly, how might ...
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17 views

Minimum sample size for non-stationary time series predictions

I'm not an expert about this topic. I'm trying to make a model to predict cpu usage. Imagine that I want to predict 5 months, What is the minimum sample size to perform the regression?. I've read a ...