# Tagged Questions

Bias, in a statistical framework, means that an estimate of a parameter has an expected value that is not equal to the actual parameter value. There is often a tradeoff between bias and variance - low variance estimators may be more biased than high variance ones.

1k views

### Why is bias affected when a clinical trial is terminated at an early stage?

An interim analysis is an analysis of the data at one or more time points prior the official close of the study with the intention of, e.g., possibly terminating the study early. According to ...
667 views

### Is there a graphical representation of bias-variance tradeoff in linear regression?

I am suffering from a blackout. I was presented the following picture to showcase the bias-variance tradeoff in the context of linear regression: I can see that none of the two models is a good fit ...
328 views

### Does stepwise regression provide a biased estimate of population r-square?

In psychology and other fields a form of stepwise regression is often employed that involves the following: Look at remaining predictors (there are none in the model at first) and identify the ...
464 views

### Parameter estimation of exponential distribution with biased sampling

I want to calculate the parameter $\lambda$ of the exponential distribution $e^{-\lambda x}$ from a sample population taken out of this distribution under biased conditions. As far as I know, for a ...
257 views

157 views

### Perfect sampling from a huge dataset

I am working with a binary predictive model for data that belongs to A and B. The learning sample that I am using contains 6000 row that belongs to group A and 1000 row that belongs to group B. I ...
151 views

### What is the estimation bias of the top estimate in a list sorted by value?

Let's make the problem as simple as possible. Assume two related random variables, $X_1$ and $X_2$. On the basis of some data we estimate their true means $\mu_{X_1}$ and $\mu_{X_2}$ by sample means ...
238 views

### Expected value of the natural log of a ratio of variances [closed]

I am dealing with a one-way random effects model and am looking for the $E(\ln(\hat{\sigma}_\alpha^2/\hat{\sigma}^2))$ where $\hat{\sigma}_\alpha^2$ is the estimate of the between group variance and ...
402 views

81 views

### Leave-one-out cross validation: Relatively unbiased estimate of generalization performance?

I have read that leave-one-out cross-validation provides a relatively “unbiased estimate of the true generalization performance” (e.g. here) and that this is an advantageous property of the ...
79 views

### Correcting biased polling

Let's say I'm polling for a binary election in different states with known biases. Furthermore, let's say I only manage to poll only a small sample of people in each of these states. How would you ...
118 views

### When to use B'' or B''D as a measure of response bias?

I hope this is not a stupid question, but here it goes: Based on information from Macmillan and Creelman's Detection Theory (2005) and Pallier's R-code that I found here, Computing discriminability ...
54 views

### Proper Sampling - can I collect a two-group sample this way without issues?

I need to collect a two group sample for a comparison analysis (perhaps using logistic regression). The population that I need to extract a sample from is all firms from country A with activities in ...
373 views

### Why must one trade off between bias and variance?

Apparently, a learning algorithm must make a trade off between bias and variance when producing a hypothesis. Bias means systematic deviation from data. Variance refers to the error due to ...
5k views

### Conceptual understanding of root mean squared error and mean bias deviation

I would like to gain a conceptual understanding of Root Mean Squared Error (RMSE) and Mean Bias Deviation (MBD). Having calculated these measures for my own comparisons of data, I've often been ...
165 views

### Can the ratio importance sampling estimate by made to be unbiased with resampling?

Consider approximating the following integral: $$\mathcal{Z} = \int h(x) \pi(x) dx$$ Where $\pi$ is known only up to a normalizing constant, that is, $\pi(x) = \hat{\pi}(x)/\mathcal{Z}_\pi$. We can ...
115 views

### How to assess whether experimental measurements obtained from different technicians are biased?

Suppose I have a list of measurements from an experiment; for example, 34 31 55 18 19 22 44 48 23 . . . But I then learn that these experiments were conducted by two different technicians, so I ...
97 views

### Remove data starting before defined start date for survival analysis

I want to do survival analysis with a big data set. The data collection started on 1997-01-01 and is still continuing yet. However, episodes that started before ...
73 views

### What is the difference between the concept and treatment of measurement error in psychometry and in statistics?

There is some confusion with respect to the measurement error. What is the definition in statistics and definition in psychometry ? The statistics does not seem to recognize the measurement error ...
90 views

### Factoring in self selection bias

I am hoping to use some self selection survey data (it's from those awful things that pop up on the start page of a website asking if you have 5 minutes to spare). This is for business decision ...
88 views

### Omitted variable bias formula with more than one variable

For a general model $$y_{i} = \alpha + \beta_{1}X_{1} + \beta_{2}X_{2} + \epsilon_{i}$$ regressing $y_{i}$ on $X_{1}$ alone will result in $\beta_{1}$ being biased given by: plim \: ...
57 views

### Detect bias in subset of Bernoulli processes

I'm looking for advice on the best method to use to answer this question. General scenario: We have multiple testing machines A,B,C,D etc. each tests a identical randomly selected part and provides ...