**1.166 experiment-design questions.**

In regression in general and in linear regression in particular causal interpretation about parameters is sometimes permitted. At least in econometrics literature, but not only, when causal ...

My understanding of LATE was that it was the effect of a treatment on individuals who were induced to be treated by the experiment. That is, the effect on compliers. My understanding of Treatment-on-...

I am actually learning experimental design. I'm a bit confused about the overlap covariates. Could someone help me on this problem?

In ordinary least squares, for example in an experimental design case, I obtain the regression coefficents by:
$ \hat B = {({X^t}{X})}^{-1}X^ty$
Then, my null hypothesis for each coefficent is:
$...

Assume I have one variable X that I experimentally manipulate, and then measure the corresponding values obtained for another variable, Y. Assume also that the two variables are both measured along ...

Summary: Correlations does not imply causation has became mainstream. I am interested in understanding what is required for the implication to actually take place.
Detailed question:
Simple case: ...

In the multiple linear regression analysis if regressors are non-stochastic the causal interpretation of parameters is automatically permitted?
I think so, because it seems me that the model can be ...

Randomized controlled experiment is base case for causality (also) in regression.
However currently I’m analyzing the role of causality in linear regression as shown in many econometrics textbook. ...

I'm currently having trouble defining what type of ANOVA I need to run as well as how to run it correctly. This is the following setup:
I have 4 groups of 30 people doing a 2-session task (one after ...

I'm new to Latin hypercube sampling, and am trying to understand if the somewhat odd sampling that results from the Matlab function lhsdesign is a limitation of the ...

I have a data set - results (measurements) of experiments for several years. Now I want to reduce the number of experiments (to save the money, time etc.) without a big loss in precision and power.
...

I have recently come across a testing design that Adobe uses in their "Adobe Target" tool that they call "Auto-Allocation". Here is their article on the test design.
https://marketing.adobe.com/...

Suppose we have that $\left(Y(1), Y(0)\right)$ are potential outcomes with $X$ being the covariate and $Z$ the treatment assignment. Typically in causal inference, one will assume strong ignorability ...

I want to optimize parameters of a genetic algorithm in Minitab. I want to use Taguchi method. To do this, I created three random datasets (with similar seeds) and run each one five times. and ...

How sampling design is differ from experimental design?

When I have been learning how to do Factorial Designs ($2^k$ mainly) the ANOVA table would usually include the main effects, all the interaction effects if necessary, and the error. However, on one of ...

An experiment to test 2 new treatments was performed in the following setup:
Animals were divided into 2 groups: young (A) and old (B). Animals were present for 3 periods. Each group consisted of 81 ...

In the Match() function in the Matching R package, it takes in inputs like:
...

I am analyzing data that are originating from an randomized experiment and I am new to this. There was one control groups and three different treatment groups. The treatment groups are discrete and ...

I am planning to do simulation for parametric study and there are 9 parameters in total. I was suggested to use DoE to reduce the number of simulations that I need to do. I studied the basic of DoE ...

I would like to fit a Gaussian Process Regressor from sk-learn to predict values of an the objective function in order to explore behaviour and interplay between inputs.
Data points are difficult to ...

In most propensity score literature on observational studies, the ATT is usually reported and sought after. However, the ATE is usually not reported and in some cases I've read papers that claim you ...

I am trying to estimate the effect of Universal Primary Education programs on domestic violence in a sample of Sub-Saharan countries. This program has been implemented in a different year in each ...

I am wondering if anyone would have a succinct way of describing the differences between the two. My understanding is that the Fisherian way is non-parametric and relies on the randomization test to ...

I'm confused about how to decide blocking, and what that means for experimenting with it. I've seen other questions on the site and don't feel that they answer this, I think this is more basic.
For ...

I know the question is a very elementary one, but I simply cannot understand the difference other than the fact that an SRS is a form of Multi-Stage Sampling. Can anyone provide a simple example(s) to ...

Consider a completely randomized design, where every unit is randomly assigned to a treatment group. Let's say we have 30 observations and 3 treatment groups. When we choose one observation at random, ...

In my research I want to employ a choice experiment using factorial design. However, I struggle to derive a fractional design from the full factorial design.
There are 9 factors on 2 levels, which ...

I have been researching for my thesis/dissertation but I guess my knowledge about this is not so wide. I am just quite confused about my model, so if you think this question is easy to answer just ...

I'm looking at Latin Squares. I've seen standard Latin squares, and Latin squares when the rows are randomised, then columns are randomised.
When would one be used over the other?
It seems as ...

In the Matching package in R, one can conduct propensity score matching if propensity scores are passed to the ...

I know that a cross-over experiment (of any number of treatments/levels) necessarily has a repeated-measures design, but that not all repeated-measures designs are cross-overs. However, I wasn't able ...

I'm running an experiment and want to use the Causal Impact function to assess how well it performs.
I have 10 different cities. I'm looking to find out what is the best method for choosing which ...

I want to collect evidence of validation for an assessment tool I have been working on. The tool is developed as a support tool for an expert evaluator to reduce the inherent subjective impact. I am ...

I have conducted an experimental study, with 1 within-variable (time: T1 and T2) and 1 between-variable (group: control and treatment), measuring just one dependent variable.
I understand that this ...

In observational studies, one can use the Rubin Causal Model to retrieve unbiased estimates, which usually there is a statement that is usually required which states that:
$$
(Y(1), Y(0)) \perp T \...

In Rosenbaum's 1983 paper, he states that "in a randomized trial, the propensity score is a known function so that there exists one accepted specification."
I am wondering what this specification is ...

I'm trying to figure out the best way to analyse the following clinical trial:
Group1: Healthy individuals
Group2: Diseased individuals
Both groups follow the same intervention and are tested pre- ...

I need to determine if an intervention had an effect. In the experimental design, measures were taken at three points in time: pre-test, post-test #1 and post-test #2. One group (group A) received the ...

I'm running a economic experiment. From a previous pilot I already know which size of treatment-effect I can expect. Each participant plays 20 rounds, so it't a repeated measures approach. I want to ...

I'm in the process of designing a BACI experiment for assessing the effect of a forthcoming hydro-electric power (HEP) development on a rare species of moss. To help decide on a final experimental ...

I'm not sure I understand this concept. In $2^k$ designs, the independent variables have only two values and are coded as either being -1 (low value) or +1 (high value).
We can add a center point to ...

I am doing a quasi-natural experiment in which I am looking at the implication of government policy in India on the performance of companies. Unfortunately, almost all of the companies in my sample ...

I am analyzing some patient data for a medical study that has a duration of several years.
Once a year, the patients are expected to visit the doctor, where they get four treatments, say A, B, C, D. ...

I read in a footnote in a paper that for the observational study setting in causal inference to hold, the outcomes, treatments and covariates must be iid. Specifically, if $Y_i$, $T_i$, $X_i$ are ...

The problem:
I have N (~500) black boxes which each receive an input and output a noisy reward signal. The reward signal is non-stationary and heteroscedastic, but can be assumed stationary over short ...

Hello I would like to know, whether my residual vs fitted plot is okay ie does not violate the normality assumption
The design is a random block design
as well as the histogram seems to be binomial ...

I am having some difficulty understanding the difference between and identifying an observational vs quasi-experimental design. From my understanding, an observational study is one in which the ...

I have a list of patient samples that were tested at 3 clinical sites; for site 1, reagent lots 1 and 2 were applied; for site 2, reagent lots 1 and 3 were applied; for site 3, reagent lots 2 and 3 ...

I am working on designing some chemical experiments, with the goal (for now) to optimize reaction yield.
I intend to use principal component scores in order to investigate solvents, Lewis acids etc. ...

- anova
- r
- statistical-significance
- hypothesis-testing
- regression
- repeated-measures
- self-study
- fractional-factorial
- mixed-model
- sampling
- t-test
- causality
- random-allocation
- mathematical-statistics
- sample-size
- references
- blocking
- inference
- biostatistics
- power-analysis
- multiple-comparisons
- logistic
- survey
- clinical-trials
- multivariate-analysis

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