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1 vote

Is partial correlation analysis in spss reasonable

Several things. First, Pearson's correlation $r$ does not strictly assume normality of the variables themselves (e.g., for interpretation). The normality assumptions only comes into play when ...
Preston Botter's user avatar
0 votes

How does whitening or decorrelation help machine learning models?

Inputing 2 (and more) correlated features (known to be multicollinear features) to the model you inflate variance of the model's output but in order to create good model you should strive to dicrease ...
JeeyCi's user avatar
  • 191
1 vote

DEPENDENCE AND CORRELATION. biostatistic italian test

I wonder if something has been lost in the translation from Italian. In the translation, however, I do not see a correct answer, because the answer is that dependent variables do not have to be ...
Dave's user avatar
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1 vote

Can I answer the reviewer's questions about the potential mediators in this way?

I would put "significant" between "no" and "correlation" and I would include the effect size (in this case, the correlation coefficients). And I'd take out "that ...
Peter Flom's user avatar
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1 vote

Obtaining P value in LASSO regularized linear regression showing that the model is generalizable

It sounds like your supervisor wants to show p-values for coefficients similar to those that you would show for unpenalized regression. You can't just plug the selected predictors into an unpenalized ...
EdM's user avatar
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0 votes

correlation range between y and two variables x1 and x2

Let's assume, without loss of generality, all data are standardised into z-scores. The data generating equation for y can then be written as: $y = b_1*x_1 + b_2*x_2 + e $ using more common notation. ...
BenP's user avatar
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2 votes

$\rho( A, B ) = 0.9999$, $\rho( X, Y ) = 0.9999$, $\sigma_A = \sigma_X$, $\sigma_B = \sigma_Y$, but $\rho( A - B, X - Y) = 0.88$

It's worth noticing what $A-B$ and $X-Y$ refer to. Each is essentially the random noise that differs between the two members of each pair. It's frankly quite surprising to me that the random noise of ...
Noah's user avatar
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1 vote

$\rho( A, B ) = 0.9999$, $\rho( X, Y ) = 0.9999$, $\sigma_A = \sigma_X$, $\sigma_B = \sigma_Y$, but $\rho( A - B, X - Y) = 0.88$

Your second sentence $A$ and $X$, $B$ and $Y$ are really almost just two pairs of near-identical time series does not necessarily follow from the first statement. Consider this example in R. I define ...
Alex J's user avatar
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4 votes

Finding the most important factor driving the target in a regression problem

Computing variable importance measures without computing confidence intervals for them is highly misleading and ignores the true difficulty of the task. An honest analysis will find that it is almost ...
Frank Harrell's user avatar
2 votes

How does one verify causation?

Detecting causality with uncontrolled observation You are correct that causality can be inferred from a properly constructed experiment in which we impose randomisation on the "potential-cause&...
Ben's user avatar
  • 123k
2 votes

Multiple regression model and correlation between predictors

Adding to Shawn's excellent answer (+1): First: Models don't "know" things. Second: The question in the book is clearly about real data and Shawn did a great job analyzing that data. However,...
Peter Flom's user avatar
  • 117k
0 votes

Correlate two variables, with many (0,0) values?

You should consider a binary regression, logit or probit. You can use the difference in probability between two groups to assess the effect or association.
DrJerryTAO's user avatar
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3 votes
Accepted

Multiple regression model and correlation between predictors

Setting their causal assumptions to the side (which aren't well explained in this part of the book), the correlation between radio spending and sales is more than double that of newspaper spending ...
Shawn Hemelstrand's user avatar
0 votes
Accepted

What is the best way to calculate confidence interval for spearman correlation by bootstrapping?

There are a number of issues with your approach, not just with the confidence interval itself: A bootstrap is usually performed by resampling an observed sample. You draw new samples from a ...
PBulls's user avatar
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0 votes

What is the best way to calculate confidence interval for spearman correlation by bootstrapping?

I'm not sure if you took it into account based on only the code you provided, but note that when bootstrapping for a CI for correlation, you have to bootstrap the dependence between the 2 variables as ...
Mathemagician777's user avatar
0 votes

How to handle correlated variables before using Recursive Feature Elimination?

Tree classifiers typically use features independently (univariate) for node splits and are not really multivariate. Thus, they're not likely to knock down the importance score of a feature because it'...
Leif Peterson's user avatar
2 votes

What kind of correlation is this?

As @Dave and @ttnphns point out in the comments, the plot does not really communicate anything because nothing on the graph indicates the number of points sharing the same coordinates (i.e., $[x,y]$ ...
Preston Botter's user avatar
0 votes

Mixed model in lme4 package is singular

As reported there are many reasons for singularity. Your example is not reproducible for the lack of data. Could you provide some characteristics of the data e.g. the levels of each factors and the ...
Alessio's user avatar
  • 11
1 vote

Partial Correlation and 1 Categorical Control Variable with 3 Categories

For starters, you don't need normally distributed data to run a correlation. Common correlational measures like Pearson or Spearman simply don't have this as an assumption and generally don't behave ...
Shawn Hemelstrand's user avatar
1 vote

Partial Correlation and 1 Categorical Control Variable with 3 Categories

When your categorical control variable has three categories, you need to construct and control for two dummy code variables to appropriately represent all three categories. In other words, both dummy ...
Christian Geiser's user avatar
0 votes

Correlation vs Euclidean distance as measures of similarity or closeness between data points with an outlier

$(1,2,3,4)$ and $(1000, 2000, 3000, 4000)$ have a perfect correlation of $1$, yet the Euclidean distance between them is rather large. $(1,2,3,4)$ and $(1.1, 1.9, 2.7, 4.2)$ have am imperfect ...
Dave's user avatar
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2 votes
Accepted

How to account for confounders in a simple correlation analysis?

Two ideas that come to mind are regression and partial correlations. The latter is more precisely an answer to your question, Regression assumes that one variable is dependent and the others are ...
Peter Flom's user avatar
  • 117k
1 vote

What is the best correlation that I can use in order to determine the relationship of these 2 variables?

I am making an assumption that your two variables refer to two treatment states, say a control group and a treatment group. In that case, your Var1 and Var2 are really one variable that indicates the ...
Dave's user avatar
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0 votes
Accepted

Deciphering and computing the limiting value of Chatterjee's xicor?

In order to mark this question as answered: Yes, the formulation with conditional probabilities is equivalent to Chatterjee's original formulation. Interestingly, for continuous $Y$, some of the ...
cdalitz's user avatar
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1 vote

Sample many correlated random matrices all with the same pairwise correlation coefficient

Most methods assume your $\mathbf{A}_1, \mathbf{A}_2, \ldots, \mathbf{A}_K$ matrices are instead $n$-length vectors $\mathbf{x}_1, \mathbf{x}_2, \ldots, \mathbf{x}_p$, which form an $n \times p$ data ...
Leif Peterson's user avatar
1 vote

Everyday life example of spurious cause and effect relation

A nice example is the following. In the Netherlands (maybe in other countries as well?) children are sometimes told that storks bring new babies. These birds arrive in the Netherlands during spring ...
1 vote
Accepted

Everyday life example of spurious cause and effect relation

Some examples: The name of a soccer team and daily temperature. Card faces and the speed of drivers nearby. School type in New York and number of monthly books sold in Texas. The example from a coin ...

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