Questions tagged [random-allocation]
The process of randomly allocating subjects (often in the context of a clinical trial) or other experimental units into two or more conditions.
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Implementing permutation tests in randomized controlled trials with repeated measures
I am trying to implement a permutation test to use for testing treatment effects in a repeated measures RCT-design. Unfortunately I am having some trouble understanding how to design a correct ...
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Assignment rules in randomization experiment for causal inference
I'm learning the Casual Inference material on Coursera. I have a question about the following assignment rules in randomization experiment. The first page is for the letter notations. Briefly speaking,...
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Why use a stratified log-rank test if we balance over strata anyway?
When comparing survival data over time, we can use the log-rank test. An extension of this is the stratified log-rank test, which adjusts for variables.
Let's say we wanted to adjust for the effect of ...
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In a stratified RCT, should strata be combined if a too small sample size is attained in randomization?
My question refers to a situation where the number of participants in some strata is unexpectedly low. Should randomization proceed in the same way as declared in the Protocol, i.e. by performing ...
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Analysis of treatment effect with partially non-randomized groups
I have conducted an experiment in which participants were randomly assigned to six groups:
Control group
Control group with additional information about problem
Pre-set treatment group
Pre-set ...
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How to code a dummy variable for time in a difference in difference model in R?
I am trying to do a difference in difference analysis on data from a randomized controlled trial where the control and treatment occurred during the exact same time period (treatment was administered ...
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What kind of model to optimize the allocation a ressource in the context of time to event outcome?
I have a list of N patients that are competing for one treatment at each time. A treatment becomes available at times t=1,...,T.
I want to build a model that can take the time-varying characteristics ...
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How to combine observational and experimental data?
I’m trying to figure out the effects of system changes on user long-term revenue (over a 12-month period, say) for an online platform.
I have a lot of observational data, so I fitted a model that ...
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What are advantages and disadvantages of bernoulli assignment/randomization?
This is good explanation for what is Bernoulli assignment is.
For treatment assignment, what is the difference between Bernoulli assignment vs. completely randomized assignment?
I am wondering, what ...
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How to deal with large combinations of factors
I am faced with a new problem that I cannot really tackle with the way I usually do my analyses and would appreciate any input you may have.
The research goal is to identify the factors and ...
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Quasi-experiment analysis
I have 5-year sales information from a grocery store in Canada. I want to check the effect of an online campaign that happened in 2017 on food sales. My treatment group is people living in urban areas....
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Should Astra Zeneca's results be discounted?
This question is in regard to Astro Zeneca's phase 3 clinical trial on the effectiveness of their COVID-19 vaccine. Patients were randomized to a two dose treatment group compared to a two dose ...
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Dropping Missing Observations under MAR Assumption
Some of the outcome data in my RCT data set are missing. I believe that the missing data mechanism is missing at random (MAR) as the observed characteristics significantly differ between the missing ...
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Why adjusting for randomization stratification factors in the model improves the precision of estimators for treatment effect?
I assume you will already get balanced treatment assignment within the randomization strata. Why would we still gain improvement in precision by adjusting for these factors in the model? Does not ...
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Block design or completely randomized?
I have 5 conditions in my experiment: A,B,C,D,E and my sample size is 200 subjects.
I want to have 40 subjects per condition, so I assign a condition to a person randomly without replacement.
E.g. ...
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How to check if randomization was proper
Randomized controlled trial (RCT), where participants are randomly allocated to 2 or more groups and given different treatments or interventions, to evaluate which one is better, are commonly ...
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Re-randomization in Experimental Design
I am struggling to synthesize the objections to re-randomization in experiments when it is costless and the criteria are pre-specified and regression is not an option. This came up in a related ...
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Experimental Design Problem with Goofy Constraints
I am having trouble designing an experiment. I will give a hypothetical example that shares the main features of my actual problem.
Suppose there are:
$M$ meadows, indexed by $m={1,...,M}$, where $M \...
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1answer
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How many unit are necessary in randomized experiment?
Let's say we want to conduct an experiment with binary treatment.
How do I decide how many units do I need to assing the treatment to, to get internally valid results? I understand that you need to ...
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Is it possible to to have more than 2 groups for biased coin randomization? If no, is there any modifications supporting multiple groups?
Is it possible to have more than 2 groups for biased coin randomization?
If no, is there any modifications of biased coin randomization supporting multiple groups?
This is my R code for generating ...
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How to do randomization check?
I am struggling to find the most effective way to check randomization within my experiment. I have a single factor design with two moderators and two DVs. My IV is type of persuasion (0 direct ...
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1answer
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Do I have to randomize all drug trials?
This thought experiment I came up with has been bugging me. Let's say I want to test the effectiveness of Drug A vs Drug B on reading speed (no placebo necessary). I KNOW for a fact that the effects ...
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Matching / Scoring in an Experiment, using instrumental variable (IV) regression for LATEs
Maybe this is better suited here, than in economics. I don't know and please excuse the Econ language, I cannot do any better.
I did an experiment with random assignment to two treatment groups and ...
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Aggregate effects of randomized experiment
Consider the following two-equation model for observational data from a randomized experiment:
(1) $y_{ij} = \alpha + \beta D_{ij} + \gamma X_{j} + \varepsilon_{ij}$
(2) $D_{ij} = \gamma + \delta ...
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Combining two studies of different types
Initial Setup
In a specific experimental design, there are two treatments and two study sites. Suppose we have the model
\begin{align*}
Y_{ijk} = \beta^\intercal X_{ijk} + \mu_i + \nu_j + \eta_{ij} + ...
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Reference for flawed randomized controlled trial
For a seminar, I am preparing an overview of advantages and shortcomings of randomized control trials (RCT; one shortcoming is, for example, often a limited external validity).
To illustrate ...
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Minimization randomisation in trial, what to do if dropout or missing data?
I have been asked a question on minimization randomisation in a randomised control trial. If the randomisation has allocated thirty participants to sham or treatment, but then subsequently it is ...
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1answer
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Advantages/disadvantages of fractional factorial design vs completely randomized design
I'm new to the design of experiments (DoE) and will be running a screening experiment to estimate the effect of a large number of binary independent variables (approximately 10) on a single continuous ...
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1answer
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Analysing stratified random sample
Let's say I am analysing an experimental design with treatment and control group which was based on random sampling design stratified on a number of covariates. When analysing the data I see two ...
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1answer
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What sample size is needed for randomization to be meaningful?
This study randomised 17 participants to 3 treatment arms. What sample size is needed for randomization to be meaningful? As an extreme example, randomly assigning 4 individuals to 2 treatment groups ...
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Controlling the allocation bias in small RCT
In order to contain the allocation bias, I would like to understand if it is possible to have a randomization process during the patients enrollement controlling ...
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1answer
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Not including main effect term in subgroup analysis?
I know there are plenty of previous Cross Validated posts regarding if one must include the main effect term if the interaction term is included. The general consensus is: no if you have a very good ...
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how to do re-randomization test for trials used adaptive minimization with unequal allocation?
Re-randomization test is often chosen to validate the results from a study was randomized by adaptive minimization. In the case of of unequal allocation (like 2:1), it is more complicated because the ...
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Randomization + Power calculation for Geo experiments
Im working on performing experiment design for a retail company where we will be holding out certain markets (stores) from a treatment (say, a flyer or outdoor ads).
1) How do we perform power ...
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Does the t-test require randomization?
Can I use t test for a non-equivalent quasi-experimemtal design? As there is no randomization, can it violate the assumptions of the t-test? What statistical technique should I use?
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Balanced randomization within clusters
I was hoping someone could point me in the right direction on a randomization method. We want to randomize teachers to receive an educational intervention. The catch is that we have a number of ...
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1answer
406 views
Test for equivalence after sampling into test groups
I want to test the effects of different versions of treatment across multiple test groups of a given population. In order to do that, I want to randomly sample my population into, let's say, 4 groups ...
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1answer
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Gibbs sampling allocations for time dependent observations from this model
I observe $N$ observations $\{x_{1,t_1}, \dots, x_{N,t_N}\}$ from a $k$ component Gaussian Mixture model. The $i$th observation is seen at time stamp $t_i$ and is distributed such that each $x_{i,t_i}|...
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Randomization in clinical trials
Randomization in clinical trials is a phenomena where each individual has equal chance to receive a treatment. How can you express randomization mathematically.
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Unbalanced second-wave recruitment in experimental research
I am working on a consult for a behavioral researcher's ongoing project. The current study uses three experimental conditions (A, B, & C), each with roughly-equal sample sizes (~n) at current. ...
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How does the “Carlisle method” work? (used to detect improper randomization in studies)
The NPR news article Errors Trigger Retraction Of Study On Mediterranean Diet's Heart Benefits refers to something it calls the "Carlisle method" of analyzing results of published studies to look for ...
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The Mediterranean diet - statistics issues with the updated paper
In 2013, a group of researchers published a paper with results on a randomized trial of the Mediterranean diet, finding that it appears to have significant health benefits. Today, they retracted ...
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Experimental Design in A/B Tests
I want to A/B test two separate back-end recommendation logic (A and B) but I'm not sure which method works best (from a statistical standpoint). Here's how my application works:
User goes to my ...
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1answer
136 views
Systematic allocation of treatment: is there a chance of biasing a design?
When we speak of the benefits of randomization, we talk about the balance of covariates so as to mitigate the possible confounding due to selection of treatment. That is, if a design were replicated ...
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How does randomisation balance known and unknown heterogeneity?
Randomised controlled trials are understood to balance known and unknown heterogeneity across groups. Beyond the a posteriori point that 'randomisation looks like it balances groups' how do we know it ...
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135 views
Best way to do block randomisation with covariates?
I have a set of $n$ objects for an experiment and I want to randomise them into a control group and treatment group with fixed sizes. I would like to use block randomisation to balance covariates, in ...
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For propensity score matching on binary outcome variables, why can the effect of treatment only be reported as the ATT instead of the ATE?
I read in this paper An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies, that
"If the outcome is dichotomous (self-report of the presence ...
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2answers
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What has to be true of controls (main effects and interactions) for them to be included in experimental analysis?
Consider a simple cross-sectional regression model,
$$y = \alpha + \beta \cdot T + \gamma \cdot x + \delta \cdot x \times T + \varepsilon,$$
where $T$ is a binary randomized treatment indicator, and ...
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1answer
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How would I analyze this sugar-elimination Quantified Self experiment?
I'm testing whether sugar consumption is making my stomach upset, with an unknown lag.
My basic plan is:
Get 7 sugarfree and 7 regular, or 'sugarfull' Grape Powerades
Label 14 paper bags with ...
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1answer
111 views
Assign subjects into groups so that group means are as similar as possible
I have some subjects from I have measured a variable (body weight). I want to do a case-control experiment where I will do an intervention on one of the groups (Experimental). I'd like for the group ...
