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

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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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2answers
15 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
13 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 ...
2
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1answer
67 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 ...
3
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1answer
95 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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1answer
100 views

Why do we need r squared?

In linear regression, the r squared value is the square of the correlation between predicted values and observed values. But why do we need the r squared value? Why not just use the correlation ...
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2answers
32 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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0answers
21 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 ...
2
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1answer
57 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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12 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 ...
2
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1answer
57 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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25 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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25 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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1answer
35 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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0answers
8 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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0answers
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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1answer
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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1answer
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 ...
2
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2answers
114 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
39 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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0answers
29 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
1
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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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1answer
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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25 views

A priori justification for using a quartic regression

I am reviewing some papers relating school performance to socio-economic background: ...
0
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1answer
26 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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0answers
25 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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2answers
232 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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12 views

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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3answers
40 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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0answers
12 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 ...
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0answers
16 views

Untransforming unbiased estimates

Suppose I have some measured experimental data and I want to fit it to a power law of the form $y=ax^b$. Suppose I transform the data to log-log space and then I fit a straight line of the form ...
0
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1answer
28 views

Compare regression slopes of repeated measures linear regression

In my design, I have two groups of subjects and every subject is tested in four different conditions. So, I have a within-subject factor ('span_num', which ranges from 0 to 3) and a between-subject ...
0
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1answer
21 views

How to format multi-row time series data for LIBSVM regression

I would have expected this to be covered in detail by the LIBSVM tutorial but after hours of wasting time googling for answers I've had to throw in the towel. What I am trying to do is rather trivial ...
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29 views

Need to use a percentage as a independent var in regression

This is my first question! My firm takes boxes of documents, preps them (removing staples, taping torn documents), and then scans the documents. I want to calculate what effect staples and torn ...
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14 views

Line with discontinuous sigmoid function in half-normal residuals plot

In R, I've plotted the half-normal residuals for a few different models, i.e. halfnorm(residuals(model_object))) I notice that one plot takes a distinct S-shape ...
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1answer
33 views

Principal component (PC) as a substitute for colinear covariates?

I am working on a spatial linear regression and I can tell there is collinearity between covariates. Can I use PCA (Principal Component Analysis) images instead of original covariates to estimate the ...
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0answers
38 views

Help with complex model formula in lmer (lme4) for R

Most examples about lmer formula description in R target rather simple study designs. However, sometimes one is confronted with more complex designs and there is no ...
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90 views

Exploratory regression analysis for data with missing values

Recently I have performed an exploratory regression analysis, using lavaan R package and observed the following output with some warning messages in it. I have the ...
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1answer
39 views

In OLS is it methodologically correct to use the variance of a variable as an explanatory variable?

Are some OLS assumptions not satisfied if I use the variance of a variable as a proxy of uncertainty in a regression? For instance, would it be methodologically correct if I use moving averages of ...
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0answers
13 views

How to compare fit of discrete process with discrete underlying process?

I am basically looking for an equivalent to something like an $\mathbb{R}^2$ for a model on a dataset that is itself simply a collection of points. That is, if my data set is (trivial example): ...
0
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1answer
26 views

Mixed model in SPSS with random effect and repeated measures

I am working on analyzing a dataset that involves repeated measures data. The data was previously analyzed by a colleague using custom code written in C++, but I have expanded the dataset and am ...
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24 views

Is it possible to calculate 95% confidence limits of a predicted value of a regression equation when we don't have the raw data?

Reading a paper, I realized that a polynomial regression equation was published with its associated standard error and sample size. That regression relates enamel thickness ($y$) and enamel formation ...
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0answers
23 views

Regression: Finding the vector explaining most variance in 3D space

I have a specific regression problem of which I am not sure how to solve it. We have a dependent variable which varies depending on a certain area that is electrically stimulated in the brain. The ...
0
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1answer
42 views

Linear regession problem

I am doing a simple linear regression on SPSS and have run Spearman and Pearson tests which came out at .40's Now on the linear regression my B and bets have come out negative I am not sure what to ...
1
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1answer
28 views

How can a distribution of cross-validated $R^2$ scores be used to determine whether one model is significantly better than another?

I have two models, A and B. I have performed 10-fold cross-validation on both of them, so now I have 10 $R^2$ scores for each. How can I determine whether one is significantly better than the other? ...
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0answers
32 views

Should I use log transformation for my linear regression? [duplicate]

I am modeling commissions earned based on non sales data. My equation looks like this: commissions = Number of times logged into the system + ... (many binary ...
0
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0answers
36 views

Propensity to purchase using regression analysis in R [closed]

I have a dataset with a sample snapshot of it looking like this: ...
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0answers
10 views

Single Categorical DV (3 levels), and Single Continuous Repeated Measure IV: which test?

I'm a Ph.D. psych student and am having trouble finding information on which test to use for a continuous repeated measures IV and categorical DV. I would really appreciate some help with this. The ...