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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Right type of randomization / random allocation for low base rates

so I have a question on the correct "name" for the random-allocation to one of two treatment groups or one control group. We designed two interventions (readings material): one on ...
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Bootstrapping confidence intervals in randomization model and population model

Ernst 2004 shows that the permutation tests in the random assignment scheme (e.g., controlled experiment) and in the random sampling scheme (e.g., observational study) share the same constructing ...
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In a randomized trial, should we exclude random intercepts and use only slopes?

Let's say I have a longitudinal study, with patients assessed at several time points, which goal is to compare the treatment vs. placebo. If, theoretically, I used a mixed model to analyse the ...
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AB Test, Experimental Design based on Machine Learning Output

Looking for the best way to set up an AB test. Scenario is that the online product I am working with has logged in users that pay a monthly fee, and they can upgrade to get access to more features. ...
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Balance checking (using discrete variables)

Context I'm doing a field intervention, with 4 treatments and 1 control. I have done a stratified randomization beforehand to ensure that demographic characteristics (gender, age, income group) are ...
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RCT using simple Randomisation, can extra participants be added?

I have been asked to perform the randomisation for a small RCT using simple randomisation. There are 100 individuals to randomise to one of two arms (control vs intervention). The researchers have not ...
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Inference for the average treatment effect for Bernoulli trial

In the book of Imbens and Rubin, they discuss four common classes of assignment mechanisms that fit into this framework: Bernoulli trials, completely randomized experiments, stratified randomized ...
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Are the arguments that placebo can be unethical mistaken?

There seem to be two ideas of placebo - or the treatment received by a placebo group: A "simulation" of a treatment using saline or sugar pill so that subjects in a clinical trial can be ...
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preference between completely randomized or stratified/paired randomized design under covariate not predicting outcomes?

Consider potential outcome of $i-$th unit $Y_i=(Y_i(0),Y_i(1))$ with $0$ as control and $1$ as treatment and say $X_i$ is the only covariate associated to $i-$th unit. Assume $X_i$ does not predict $...
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Comparing treatments when there is imperfect compliance

Imagine a situation where we have a 2x2 cross-randomized program with imperfect compliance to the treatment arms. Thus, units are assigned to treatment A, treatment B, or both treatments. Once they ...
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How to forecast a rental weekly sales demand using a 4 year history data?

I need to estimate the weekly demand required for a specific product in a specific week at a specific location. I have the past 4 years daily data of each product at each location. For example: number ...
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Which test(s) should I use for RCT, 2 groups (intervention vs. comparator) and two DVs measured at multiple points (pre, post, 3, 6, 12 months)?

I am planning an RCT to evaluate the short- and long-term effectiveness of a CBT intervention. There will be two groups: intervention vs. active comparator and two outcome measures: anxiety scale and ...
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Stratified Randomization Guidance

Working on a dissertation, but still coming to grips with the concept of randomization (due to lack of experience), hope you can help to guide me as to whether I'm on the right track. I am working on ...
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Multiple comparison correction with real-valued parameter

I have a real dataset with some information about a group of people. Using this information, I can calculate the metric $d(\theta,real~data)\equiv d_{RL}(\theta)$, where $\theta$ is the metric ...
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Entropy balancing what are the gains in applying the technique?

I am developing a research that involves a model and when estimating it the coefficients were not significant. Because the hypotheses are strong, my advisor suspects that there is some problem in the ...
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My random allocation schedule list ran out - is it valid from a statistical standpoint to simply generate a new list?

Problem My random allocation schedule list was design to randomize 100 participants. 50 participants have been recruited so far and randomized to treatment A or B. A recent change to the assumptions ...
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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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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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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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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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Is it worth redoing random split several times in order to draw the 'best' control group?

My customer performs targeted marketing campaigns on subscribers. For evaluation purposes he splits target audience into target and control groups (TG, CG). He says he does this splitting randomly, ...
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Significant difference between randomized groups at baseline?

A collegaue and I are conducting a pilot study in a school, the aim of which is to assess whether an "alternative" educational tool is more or less effective than traditional teaching ...
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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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