# Tagged Questions

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### Approximate computation of a linear function

I am not sure that this is the right stackexchange site for this, but here goes: Let $d_1,\ldots,d_n$ be known real numbers, some positive, some negative. Let $v_1,\ldots,v_n$ be non-negative numbers ...
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### Is stepwise elimination of insignifcant variables invalid if applied to experimental data?

Setting: Experimental data and control-variables I want to evalute the (average) treatment effect in a randomized controlled trial. Individuals $i$ in one group received a treatment ($D_i=1$) and in ...
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### randomization test on differences

I have three treatments (A, B, and C) that I would like to compare. However, within each treatment, I have nested "high" and "low" (H and L) treatments. The values for A, B, and C must be calculated ...
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### Systematic sampling and informed consent: Does the requirement for informed consent introduce sampling bias into randomly selected samples

Probability sampling methods help reduce sampling bias. In clinical research, simple random sampling methods works well for randomised control trials, and systematic sampling methods are easy to ...
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### Randomized Intervention and endogeneity across outcomes

Community, I am looking for a proper identification strategy for a specific question which I want to answer with my data and was wondering whether anybody here would have an advise on that. My ...
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### When is there a point for using regression with controls to analyze experimental data?

Many randomized controlled trials in economics (and probably other sciences as well?) use regressions to analyze data obtained from experiments. In the simplest setup with binary treatment, assuming a ...
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### How to use permutation test to create null distribution for categorical data?

Consider a population of 1,000,000 individuals. I have examined them all and identified 1000 samples which I believe are not like others. To confirm this I analyzed the 1000 sample regarding one ...
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### Monte Carlo Methods

_I've tried using sqrt p(1-p)/n to get the standard error and then calculate the t test but for all parts I get a very large number of t so this means ...
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### Randomization scheme for rating images and assessing inter-rater reliability

Apologies for the basic question, but I'm new to the area and I'm working on a research project on rating images, and assessing the reliability of these ratings, with the following structure: There ...
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### t.test and permutation test results providing totally divergent answers

I have a data set with two classes and completely unbalanced samples sizes between the two classes. Note that even though I am showing some R code here, this is not a programming question. ...
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### Suspiciously small p-values from randomization (Fisher-Pittman) test

How are p-values calculated when using a Monte-Carlo approximation of the Fisher-Pittman test? I was under the impression[1] that $p$-values generated by randomization tests should always be of the ...
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### Experimental design: Same randomly selected stimuli versus different randomly selected stimuli in every subject

In an experiment, we’re going to present randomly generated stimuli to multiple subjects one trial at a time and measure neural responses to them. The stimuli are randomly generated to satisfy the ...
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### Deep Neural Network weight initialization

Given difficult learning task (e.g high dimensionality, inherent data complexity) Deep Neural Networks become hard to train. To ease many of the problems one might: Normalize && handpick ...
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### Can you acquaint a randomization test with any test?

I want to determine whether my randomizer works properly in a statistical test. One method to do this is a randomization test where we try all possible combinations for two groups. For example: could ...
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### Chinese Restaurant Process

I want to implement Chinese Restaurant Process representation of Dirichlet Process for random partitions. The problem setup is as follows: I have some data (customers) which I have to randomly ...
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### Randomizing Class Labels during classification to asses the feature selection results

I have a binary classification problem with thousands of variables and less than a hundred data points and class labels. The class is imbalanced (24 positive 51 negative samples). I have selected some ...
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### sampling size for binary group estimation (under randomized validation)?

Having binary groups with n members (size of several thousand or more members which can have 0 to ...
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### Non-random assignment to treatment group due to anticipation of treatment in difference-in-differences design

I have a very basic question regarding a DiD-Design. If the subjects in this design select themselves into treatment/non-treatment group because they anticipate the treatment (e.g., they want to avoid/...
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### Treatment Effect Approach and Selection Bias

Suppose to have the National Health Interview Survey data (NHIS), the health status of the observed people as outcome $y_i$, which has got different potential outcomes on the basis of a treatment ...
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### Placebo effect in randomized controlled trials (RCTs)

How does the number of intervention arms in a given RCT comparing several interventions to a placebo affect the placebo effect?
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### Extract habituation effect with randomized trials

I want to find an orientation effect in my data. I did a response time experiment with 2 conditions (congruent and incongruent response mapping [answering a-left-b-right vs. b-left-a-right]) ... Now I ...
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### Control variables in experiments

Assume you are trying to test the effect of condition X. You sample people randomly and put them in a manipulation group (condition X) and a control group (condition Y). Simultaneously you want to ...
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### Non-Randomized Block Design?

Suppose I am running a $2^2$ factorial design in two blocks. Denote the factors as A and B and the four treatment combinations as $(1), a, b$ and $ab$. Consider the blocking arrangement: ...
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### Adjust for covariables even in randomized experiments?

Randomization does not guarantee balance in an experiment. Balance is the prerequisite for causality, so theres a potential for using regression adjustment in randomized experiments. This is somewhat ...
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### Dealing with “misfits” in stratified randomizations

Suppose we're doing stratified random treatment assignment. For the sake of this question I'm going to refer to the control group as one kind of treatment so, at the most basic level, we have 2 ...
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### Experimental Design: Number of treatments and replications

I am learning about experimental design. I have been provided the following definitions: Factors: Variable(s) manipulated by researchers in order to observe response(s) Levels: Values of factors ...
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### Nonrandomized better performance

On the footnote of page 497 in Jaynes' "Probability Theory: The Logic of Science" he writes Of course, Fisher’s randomized planting methods – which we think to be not actually wrong, but ...
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### Biased coin randomization with adjustments over time

Assume an experiment that was going to consider different randomization strategies to address different challenges. The experiment involves an experimental (active treatment) and control group (usual ...
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### Would using the md5 for treatment assignment introduce any biases?

Disclaimer: I'm not sure if there's a better stackexchange for this, but since I consider experimental design an integral part of causal/statistical inference, I'm hoping this is an appropriate ...
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### About the Randomized Dependence Coefficient

In the paper The Randomized Dependence Coefficient, authors introduce a novel dependence coefficient which seem to be quite generic and powerful compared to what is present in the literature. It is ...
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### Is re-randomization valid approach to estimate statistical significance

I am a newbie in statistics and I'm taking Khan Academy course. There is one video I don't quite understand. Here's the gist. A statistican wants to know which bus gets her to work faster: A or B. ...
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### Two sample tests for stratified randomization

I have to test the difference between two samples which were selected via stratified randomization. The problem is that the samples are not independent due to randomization was stratified. How should ...
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### Is tossing a coin a fair way of randomising a group into two groups?

So myself and my uncle are having an argument over whether a coin flip is truly random. I argue it isn't because in real terms a coin tosser will always manipulate a coin so the result isnt 50/50 ...
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### Test to compare distributions using the intersection area of the densities

I have to compare several distributions, but I don't want to use Kolmogorov-Smirnov test, since I'm dealing with big data ($N > 10^{6}$) and traditional hypothesis tests end up with detecting the ...
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### Can a truly randomized procedure (e.g. random treatment allocation) result in unbalanced distributions?

Thousands of randomized trials are ongoing or in the planning. These trials rely on randomization procedures (e.g. patients being randomized to either placebo or active drugs) to yield two balanced ...
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### Why would one not stratify random assignments in a controlled trial?

With some frequency I read reports of randomized controlled trials where, despite the randomization, a baseline survey found significant between-group differences in important covariates. It seems to ...
I'm designing an experiment, in which 40 participants answer 10 questions, 5 in condition $A$ and 5 in condition $B$, and I'm interested in the difference between the two conditions. It's not clear ...