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

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Test data for regression modeling - Sales

Currently I am working on my final project at my university on building a regression model for sales data. But unfortunately I am not able to get some realistic data where I can do my analysis. I ...
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17 views

Testing correlation between two variables when there are other variables involved

I want to see if there is any correlation between number of pages in a paper and the citation it receives. If I just plot number of pages vs number of citations of a paper, I might get a correlation, ...
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17 views

Can collaborative filtering be cast as a classical regression problem?

Having the Netflix challenge in mind: collaborative filtering is typically presented as a matrix dimension reduction. My question is how does the problem relate to classical regression (supervised ...
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17 views

lm weights and the standard error

I am fairly new to R, but am experienced in other languages and also in data analysis in the physical sciences. I have a problem and will illustrate with a straight line fit using ...
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12 views

regression analysis for dataset with few predictors and few samples

I have a small pilot dataset containing experimental measurements for 12 samples, 4 numeric predictors and 1 numeric outcome variable. The goal is to obtain a first rough estimate on the extent to ...
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37 views

Identifying What Causes a Variable to Increase

Say I have a dataset with several continuous and categorical variables, and I want to identify what variables (values or properties of these variables) may cause one of the continuous variables to ...
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52 views

Treating Categorical Data as nominal or ordinal?

There is a four category classification system for individuals with HIV, labeled Stages 1, 2, 3, and 4, with higher stages indicating more advanced disease. Cell count is a continuous variable, and ...
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120 views

Does fixing coefficients in a regression make sense, and if so how to do it?

I have a generic question about whether it might sometimes make sense to fix specific regression coefficients to predetermined values. And if this makes sense in particular cases, how do you best go ...
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1answer
42 views

Linear regression of 0/1 response (Fig. 2.1 of The elements of statistical learning)

In chapter 2 ESL book authors write: Let's look at example of linear model in a classification context They fit a simple linear model $g = 0.3290614 -0.0226360\cdot x_1 + 0.2495983 \cdot x_2 + e$, ...
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9 views

beta differs from overall subgroup

I want to know whether the beta of a subgroup differs from the beta of the overall group. Both variables are dummy variabes. The overall group variable has 52 out of 267 obseverations where it takes ...
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11 views

Under-forecasting in Regression

I have to do forecasting of sales that is how much sales of a product is going to happen in a particular store. I have time series data for last two years and doing forecasting for 2014. The variables ...
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14 views

Regression with covariates on time-series data [on hold]

I have monthly data at physician level (sales and marketing activity data for last 12 months for 3000 physicians). I want to find out the impact of marketing activity on sales. There are other ...
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21 views

Interaction in regression [duplicate]

In my regression model of BMR on age (yrs) , gender (1=male, 0=female), height and weight. The regression equation obtained is: BMR = 1232.059+13.281 weight+3.954 age+192.214 male-3.471 age:gender. ...
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R programming: Lapply(split) and Model Generation [on hold]

I would like to generate and store for multiple models to subsets of my data, but am having a hard time getting the programming code to produce correct output for more than one model. I have hundreds ...
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57 views

Linear Regression with Dummy Predictor

Say there are two groups, each with n=500, with y=weight in pounds. The sample mean and sample standard deviation of weight are given: Exercise(X=1): Mean=170, SD=20 Non-Exercise(X=0): ...
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10 views

Is time-delay embedding/attractor reconstruction used in some machine learning algorithm?

I try to model/forecast blood glucose levels from my diabetes diary, so I have to deal with some 5-7 daily measurements of estimated carbohydrates, physical activity, insulin doses and measured blood ...
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16 views

Weighted Least Squares with Standardized Coefficients

I want to understand how weighted least squares regressions work to implement it in a more complex context. I think I'm a good step into that process, but I'm still wondering what the correct way to ...
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1answer
118 views

Doubts in linear regression

If a linear regression model has a constant term say 1 or 0.2, for example if the original model is $y(t) = 0.2 + ay(t-1) $, then what does this constant term imply? Will it hamper the estimates if ...
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38 views

Omitted variable bias in logistic regression vs. omitted variable bias in ordinary least squares regression

I have a question about omitted variable bias in logistic and linear regression. Say I omit some variables from a linear regression model. Pretend that those omitted variables are uncorrelated with ...
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3answers
49 views

How to Use Neural Networks to Forecast Time Series Data with Predictor Variables?

I have browsed a lot of topics here, but the ones I see were all about forecasting a single variable, depending on its historical values. Whereas I want to predict a variable, by estimating a ...
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2answers
42 views

Factor or No-factor

I am performing linear regression in R and I have a variable called diversityscore which is a value ranging from 1 to 10 indicating #activities a user performs with 1 meaning one activity to 10 ...
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1answer
93 views

Interpreting odds ratio of an ordinal regression when independent variables are negative percentages

I'm trying to express the results of an ordinal regression with a certain "perspective", and I'm confused. My dependent variable is an ordinal representing the progression in a scale of negative ...
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1answer
106 views

What location parameter is modelled by robust regression?

There is quite some number of ways how to robustly fit a linear regression model, e.g. using M-estimation based on Tukey's biweight loss or on Huber's loss, see e.g. Wikipedia. I got two questions ...
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135 views

Why do we need $R^2$?

In linear regression, the $R^2$ value is the square of the correlation between predicted values and observed values. But why do we need the $R^2$ value? Why not just use the correlation coefficient? ...
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39 views

Probability of event happening when data is aggregated with many independent events over the course of time

Let's say you have $X$ coins, each with a differing probability of landing heads (e.g. coin 1 has 10% chance of landing heads, coin 2 has 20% chance of landing heads, etc.). Now, let's say that you ...
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22 views

Linear trend in SAS using contrast

I've been struggling with this problem for a couple of hours, and I could use some advice. I have a linear regression model with two continuous predictors and a categorical one (with 4 levels). I ...
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1answer
60 views

What kind of model can I try to fit in this plot?

I have a plot like this. I wish to apply a model to this, however, I guess a linear regression model won't work on this. What I did was plot it on logarithm x and logarithm y axis as well but it ...
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13 views

Stacked Generalization Ensemble Algorithm for regression

I am using stacked generalization(Rupert 1992) for combining multiple(8) heterogeneous base learners for regression. What I understand from the pseudo codes that Train the 8 learners on 8 instances ...
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1answer
90 views

Can we skip the lower order terms in interactions? [duplicate]

This question is about three-way interaction and the possibility of applying without second lower terms with keeping the main variables in the equation not like the other questions. In fact the other ...
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26 views

How to show whether the average coefficients of determination from one regression technique are better than another across many objects?

I have 50,000 objects on which I have performed two different types of regression. Using cross validation, I obtained the average $R^2$ score from each model on each of the objects. So now I have a ...
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27 views

Confidence interval for a regression parameter via prediction

Consider a simple Poisson-regression - GLM - model. There $\exp\left(\beta\right)$s are used as Incidence Rate Ratios (IRR), but their calculation is sometimes not completely straightforward, for ...
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36 views

Regressing, analysing data with points rather than polynomial?

I am looking into making a regression of a bunch of data that is contained on some range of real numbers. In my case, x is between 0 and 1 and y is between 0 and 10. If I have 150 data points on this ...
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1answer
13 views

Using Mantel to explore relationship between geographic distance and a multivariate character

I'm working with bird songs. A song is composed of many vocal parameters [highest frequency (Hz), lower frequency(Hz), bandwidth(Hz), duration (s), number of notes, and son on....] I'm interested in ...
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43 views

Determining Relative Weights

I am looking for some recommendations and more specifics about how to do the following: Objective: To determine the weights of a number of stock valuation metrics. I am looking at doing this across ...
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19 views

lm() producing many NAs for coefficients

I am trying to run a regression using about 80 independent variables. The problem is that the last 20+ coefficients return NA. If I condense the range of data to within 60, I get coefficients for ...
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26 views

Random variable variance

I have the model $y_i=\beta_1+\beta_2 X_i+ u_i$ where $u_i\sim\text{iid } N(0,\sigma^2)$. I estimate $\beta_1$ and $\beta_2$ by drawing a straight line between the first $(x_1,y_1)$ and last dot ...
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2answers
117 views

Is residuals autocorrelation always a problem?

I read that OLS underestimates variance when residuals are autocorrelated. I see why autocorrelation would be a problem in time series analysis, in the sense that the coefficient are not efficient ...
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3answers
42 views

Covariate no longer significant after inclusion of interaction term

I'm trying to interpret some results here, and just want to make sure that my logic is sound. I'm predicting a binary outcome with a categorical predictor (gene level coded as 0, 1, or 2 dependant on ...
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31 views

Is two years enough for panel data analysis?

I have around 800 companies for only two years period. However, around 200 of them have only one year observation. Is it still possible to conduct panel data analysis with such data Thank you
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1answer
24 views

Need help doing multiple linear regression with several independent variables that are of differing levels of measurement

I am attempting to predict levels of body dissatisfaction from a number of independent variables. The dependant variable is Body dissatisfaction = overall score on a body dissatisfaction scale. The ...
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29 views

Regression using dummy variable

I would like to regress total energy expenditure on weight and gender. Is it better to consider gender as a dummy variable or find separate regression equations for men and women?
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28 views

A priori justification for using a quartic regression

I am reviewing some papers relating school performance to socio-economic background: ...
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1answer
28 views

Find the amount of variation due to another covariate

I'm trying to explain a binary outcome (cardiovascular disease) with a categorical predictor (gene level, coded as 0, 1, or 2 depending on the number of risk alleles present). I'm trying to determine ...
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27 views

Regression inconsistent results?

I have a question regarding the findings in an article which I don't fully grasp. The authors examined the relationships between variables measured at different time points. They found that a ...
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266 views

SPSS and Stata output different

I'm Stata-proficient but learning SPSS for my new position. I am using a simple dataset to do very basic regressions and comparing to see if the results are the same. They're not. I'm close, but the ...
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6 views

Should I run Hierarchical regression to test moderation? Why?

I am an undergraduate student who currently preparing for my thesis paper. In my design, there is total 4 variable (1 predictor, 1 moderator and 1 outcome variable, all of them is in continuous ...
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Question about basic moderation analysis

Assume a 2x2 between-subjects experimental design (FACTOR1 and FACTOR2, which are both categorical), and there's also 2 continuous dependent variables, DV1 and DV2. Assume that on ANOVA on DV1 reveals ...
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47 views

Correlation using Logistic Regression and Pearson

I am so sorry, I am beginner in statistic analysis, I have project using R to analyze the correlation between dependent variables and independents variables. In this case I have two dependent ...
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15 views

Test if a slope falls within a back-transformed (log) prediction interval

I'm trying to test the hypothesis that the relationship (slope) between second molar tooth size and overall molar tooth size is 0.33 (in species of rodents), using generalized least squares regression ...