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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How does two-step randomization affect the variance partitioning in an ANOVA?

I am trying to understand how multi-step randomization affects ANOVA results. For example, I can think of a pair of experiments, both with 2 crossed factors, FxG. In the first experiment, shown on ...
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Current examples where randomized studies yield different results than observational studies

I have been reading the following paper by G. Smith (2002). I found it rather surprising. Some excerpts: Promising epidemiological and laboratory findings led to a paper published in 1981 in Nature ...
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Excluding participants due to issue in randomisation?

I have been carrying a study and due to a human error in the randomisation process, instead of getting equal sized groups (I have 8 and aimed to have 100 per group), I now have around 90-100 ...
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Why is it acceptable to use the Sum of Squares of an Interaction as the Sum of Squares Error in a Randomized Complete Block Design?

Take for example the RCB design [Y = I + B + F + E], where... Y is the response I is the overall intercept B is a blocking factor with two levels F is a treatment factor with two levels E represents ...
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What statistical methodologies are currently used in clinical trials to estimate treatment effects?

For example, are more novel methodologies for obtaining unbiased treatment effect estimates, like Targeted Maximum Likelihood Estimation, being utilized in randomized controlled experiments in ...
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What is a "split-body" RCT?

I am reading the RCT Wikipedia page, in particular the classification by study design. There are described four types of RCT: (i) parallel groups (ii) crossover (iii) cluster (iv) factorial. Then ...
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How many types of randomization are there? And how they each dealt with in the experiment's design or statistical analysis?

I am trying to understand randomization in experiment design, and am very confused, because there appear to be several types of randomization possible. For example, for a Categorical Factor with Non-...
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Research design: Term for assigning participants to groups depending on day (instead of randomisation)

I am looking for the term used to describe when participants are assigned to experiment groups based on the day. We tested several classes in a training centre and selected randomly which class should ...
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Gender randomization in clinical studies

Hi i'm sorry if this has been asked before but I'm confused about the boundaries of gender randomization/distribution in a clinical study. I have an example study of 430 participants with multiple ...
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Balanced Allocation of Subjects to Base/Target

Lets say I'm conducting an experiment / AB test on a very volatile measure. I have a set of good estimators for this measure, which is known to me at the moment I need to assign each subject/...
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Randomization method that allows for controlling for continous covariates

I have a group of patients (about 100 of them) that needs to be randomized into 2 groups (treatment and control) so that these groups were as similar as possible in terms of some (about 6-10) ...
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In an RCBD where samples are taken from different sites then allocated to treatments: block first in field or lab?

I am a soil scientist, designing an incubation experiment. I will sample soil from adjacent fields under different management. In the lab, I will subject the soils to different stresses and monitor ...
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Dealing with pre-test bias by repeated random sampling

I'm dealing with zero inflated data that has extreme volatility. I wish to randomly assign X observations/participants/subjects from the data, treat half of them with a new treatment ("target&...
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What statistical model should be used to analyze data from a randomized pretest-posttest controlled trial when subgroups exist?

I'm planning a randomized pretest-posttest controlled trial of a psychological therapy intervention group compared to an active control group on a dependent variable of interest. My population will ...
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Variance of a U-statistic with random kernel

The variance of a U-statistic $\widehat{\Theta}$ (with fixed kernel) amounts to $Var(\widehat{\Theta}) = \sum_{c=1}^m \alpha_c \kappa_c - (1 - \alpha_0)\Theta^2$, where all parameters are defined as ...
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weighted randomization

I would like to randomize subjects in two groups so that the allocation ratio is 1:1. Let's say the control group already has 5 subjects while the experimental group already has 7 subjects. Then, the ...
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Using an RCT and a retrospective cohort in the same study

I have seen that in RCT’s with very long follow up times the power of the study can be impacted by various factors in Herbet, Kasza, and Bø, 2018, and I was wondering if anyone has heard of comparing ...
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Is there a good framework for using Active Learning (reinforcement learning?) for Experimental Design?

We have a frequent problem that we deal with in a research environment that essentially boils down to finding the optimum conditions in a certain experimental space. At the moment we essentially solve ...
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Discover causal effects using OLS: does the treated and not treated group need to be similar on all observed variables?

I have one dummy variable, $D$, which equals 1 if the subject received treatment and $0$ otherwise. My outcome of interest is $Y$. For example, $D$ tells me whether the subject took the drug or a ...
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How to account for spatial and serial correlation simultaneously in a diff-in-diff estimation model?

I am trying to conduct an extension of the econometric analysis in the paper "Banking the Unbanked? Evidence from Three Countries" by Pascaline Dupas, Dean Karlan, Jonathan Robinson, and ...
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Using PCA to combine variables in a randomized trial with a baseline and a follow-up measurement

Assume that $2n$ participants have several variables measured at two times points $t_1$ (baseline) and $t_2$ (follow-up). For illustrative purposes, I will use the example of just two variables: the ...
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randomised controlled trial in regression

I am a bit confused by the assumption of randomness in regression. Taking the effects of maternal education on child mortality, is the random part referring to 1. randomly selecting respondents, or 2. ...
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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 AstraZeneca's results be discounted?

This question is in regard to AstraZeneca'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 placebo ...
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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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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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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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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 ...