Validation is the process of assessing whether the results of an analysis are likely to hold outside of the original research setting. DO NOT use this tag for discussing `validity` of a measurement or instrument -- such as that it measures what it purports to.

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45
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5answers
31k views

What is the difference between test set and validation set?

I found this confusing when I use the neural network toolbox in Matlab. It divided the raw data set into three parts: training set validation set test set I notice in many training or learning ...
26
votes
2answers
3k views

How to draw valid conclusions from “big data”?

"Big data" is everywhere in the media. Everybody says that "big data" is the big thing for 2012, e.g. KDNuggets poll on hot topics for 2012. However, I have deep concerns here. With big data, ...
9
votes
2answers
2k views

What is the procedure for “bootstrap validation” (a.k.a. “resampling cross-validation”)?

"Bootstrap validation"/"resampling cross-validation" is new to me, but was discussed by the answer to this question. I gather it involves 2 types of data: the real data and simulated data, where a ...
6
votes
3answers
2k views

What is a consistency check?

I was asked such a question as "Did you do any consistency check in your daily work?" during a phone interview for a Biostatistician position. I don't know what to answer. Any information is ...
4
votes
1answer
421 views

What is the intuition behind the variation of information (VI) metric for cluster validation?

For non-statisticians like me, it is very difficult to capture the idea of VI metric (variation of information) even after reading the relevant paper by Marina ...
4
votes
1answer
1k views

Best practices for measuring and avoiding overfitting?

I am developing automated trading systems for the stock market. The big challenge has been overfitting. Can your recommend some resources describing methods for measuring and avoiding overfitting? I ...
3
votes
1answer
283 views

Determining values of correction factor based on x bins in observed vs. actual data

I am trying to automate a problem I usually solve by hand. I have a sensor that collects data from the field. Every 6 months or so, I have to do a calibration on that sensor by collecting ...
3
votes
2answers
905 views

Validity of pseudo-panel data constructed from repeated cross sectional data as a panel data

I am looking at the repeated cross-sectional data from federal reserves, which has both panel data and repeated cross sectional data at different time-points,e.g. 2007-2009 is a panel while 2010 is a ...
4
votes
1answer
2k views

Model validation after fitting a negative binomial GLM in R

Ok, I have searched and searched and just have no clue where to start. First, what I would like to do is produce a QQ-plot (or even a readable residual plot) to look at the fit of my model. I guess ...
3
votes
2answers
448 views

Logistic regression performs better on validation data

Recently I've been building a model using logistic regression. To my suprisise LIFT chart looks better on the validation data than on the training data, the same is with ROC. All variables in the ...
2
votes
2answers
91 views

Validate a medical test

I've never done something like this before, thus I do not even know where to start with calculating whatever I need. Following scenario: We measure a medical value (Glucose) with our device, and ...
2
votes
2answers
1k views

Computing c-index for an external validation of a Cox PH model with R

First off, I'll state that I'm aware many questions get asked about the c-index. I've searched this site and others, and I haven't found an answer for my situation. I can successfully use ...
1
vote
2answers
445 views

Logistic Regression Model Validation

I am validating a logistic regression model. This is the first time i am validating a model. I am using split sampling method. I have split data randomly into two parts - 70% development and 30% ...
0
votes
0answers
66 views

How to interpret the results of bootstrapping and Monte Carlo simulation utilised to test lasso logistic regression results?

My situation: sample size: 116 binary outcome (32 events) number predictors: 42 (both continuous and categorical) predictors did not come from the top of my head; their choice was based on the ...