Questions tagged [observational-study]

An observational study involves purely observing the state of the world without manipulating it.

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7
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1answer
127 views

Recurring problem with retrospective data collection study designs I'm seeing

I've noticed a lot of medical research that I am involved in goes as follows: Collect data on 300-1000 patients, including all sorts of baseline characteristics such as BMI, age, gender and then ...
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0answers
31 views

Optimizing profitability by adjusting payment terms

I'm trying to optimize profitability by adjusting payment terms. My company sells mostly to small businesses; some of these customers receive payment terms (e.g., net 30 days) and some are required ...
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0answers
19 views

Should I use simple random sampling instead of stratified sampling when some strata have low counts?

I am designing a survey for which I would like to stratify "events" by state / province, creating $h=86$ strata for the particular dataset I'm working with. However, there are some strata with low ...
2
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1answer
25 views

IPTWs for Multi-category treatment, how to handle a multi-category mediator

I have a multi-category treatment for which selection is adjusted for using IPTWs. My concern regards a multi-category mediator that occurs post-treatment, but which also co-occurs with the outcome. ...
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1answer
14 views

How to select random data in a dataset in R [closed]

I have an excel with 5 thousand data, i want to select just 300 random datas from this dataset. what command do I use ?
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1answer
40 views

A/B Testing in observational studies

In the regime of observational studies, I am trying to understand if system A works better then system B. The task of a system is to pick products from a given cart full of products. Whether a pick ...
52
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11answers
5k views

Famous easy to understand examples of a confounding variable invalidating a study

Are there any well-known statistical studies that were originally published and thought to be valid, but later had to be thrown out due to a confounding variable that wasn't taken into account? I'm ...
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1answer
30 views

hypotheis testing in observational study with propensity score matching to reduce confounding

in observational studies, many people use propensity score matching to reduce confounding (measured co-voriates) between two groups (cohorts). But due to some unobserved confounding co-variates (not ...
0
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1answer
46 views

Non interventional studies and statistical testing

I have been part of an observational study which we also call a Non Interventional Study (NIS) which looks at a pool of subjects for whom we have 12 months data prior to starting a treatment and 12 ...
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1answer
308 views

advantages and disadvantages of IPTW vs propensity score matching?

what are the advantages and disadvantages of IPTW (Inverse Probability of Treatment Weighting) comparing to PSM (propensity score matching) in dealing with confounding variables?
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1answer
73 views

Under heterogeneous treatment effects, will the usual unconfoundedness assumption need modification for observational studies?

Suppose that a set of covariates, $X_i$ follows a distribution that is conditional on another variable, $A_i$, for $i \in \{1, \ldots N\}$ individuals. For example, $X_i$ can be income, and $A_i$ can ...
0
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1answer
41 views

For the ATT (Average Treatment Effect on the Treated), why is it usually talked about in the population perspective when it is defined w.r.t. samples?

The $ATT$ or the Average Treatment Effect on the Treated, is defined as: $$ ATT = E[Y(1) - Y(0) | T=1] $$ for potential outcomes $Y(1), Y(0)$ and treatment indicator $T \in \{0,1\}$. It is my ...
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14 views

how to use depended / non-random observations when trying to inference exponential parameter

consider this case: There is a price rate for a certain product that changes throw time, The price rate is changed every x minutes (unknown, not constant). This price has depended / non-random ...
4
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3answers
81 views

Study design question: What's the best design to assess harm of an exposure?

Was hoping to get your thoughts on a prospective study design. Here's some basic info: Population: Patients with melanoma receiving immunotherapy. Exposure: Steroids within 3 months prior to first ...
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0answers
40 views

Causal Inference in a employee churn context (difference-in-differences / Propensity score matching)

For my master thesis I'm trying to determine the causes of an employee leaving a company. Currently I'm trying to study the effect that giving a raise has on employee leaving a company or not. So my ...
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1answer
34 views

Term for observational study in which different cohorts are compared at an equivalent stage of development

I have a dataset tracking certain outcomes in school children, with all grades being sampled every year for a number of years. There are a number of study designs possible with such a dataset. As I ...
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0answers
32 views

How to calculate the mean over uneven observation times?

Possibly a very basic question, but I would really appreciate clarification from those with a strong background in stats/epi. I have a number of human patient medical records. They are retrospective ...
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0answers
16 views

Testing if number of observations in experimental conditions is statisically different

I was conducting in experiment in which i sold products on a pay-what-you-want basis in 4 different information conditions. Apart from comparing the average willingness to pay across the 4 different ...
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0answers
37 views

In causal inference, is the usual unconfoundedness assumption interpreted to apply at the unit or covariate level?

Suppose for each unit $i \in \{1, \ldots, N\}$, we have that $(Y_i(1),Y_i(0))$ are the potential outcomes, $Z_i$ is the treatment, and $X_i$ the covariates. I have seen the following two ...
2
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1answer
194 views

How exactly to evaluate Treatment effect after Matching?

In Elizabeth's Stuart's 2010 paper "Matching methods for causal inference: A review and a look forward", she states the following: "Section 5: Analysis of the Outcome: ... After the matching has ...
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0answers
31 views

Best method to investigate treatment effect after creating a Matched control group using Gentic Matching (with replacement)?

Project background: I have data on patients who received varying amounts of therapy dose during treatment of stroke-induced paralysis. I wish to investigate if there are differences in motor-function ...
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1answer
37 views

observational study vs natural experiment

I'm reading about observational studies and natural experiments. It's unclear whether there is a conceptual difference between the two terms. What is the difference between an observational study ...
2
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2answers
29 views

Matching covariate selection- should we not match on binary features where overwhelming majority of subjects fall in one category?

I am trying to investigate if there is a relation between Occupational Therapy (OT) dosage for stroke patients and patient recovery. I have separated the patients into 2 groups by the amount of ...
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1answer
74 views

After performing Matching w/ replacement, should tests to evaluate treatment effect between the matched groups include repeated subjects?

I am using Genetic Matching to infer causality from observational data. Because I am matching with replacement, the matched Control group has multiple instances of some of the same subjects. In this ...
4
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1answer
63 views

Interpretation of intercept only random effects models

I am estimating the global risk of infection risk in a population of patients, but these patients are clustered in hospitals and wards/departments. If I just take the crude prevalence (infected ...
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1answer
170 views

In the superpopulation framework of causal inference, what is the necessity of assuming the outcomes, treatment and covariates are jointly iid?

In the textbook "Causal Inference for Statistics" by Rubin and Imbens, the following argument is made on pg. 39: "In part of this text we view our sample of size N as a random sample from an ...
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1answer
38 views

R- Trouble understanding what loss function is being used by Genmatch (genetic matching) algorithm

I am having some trouble understanding what loss function is being minimized to ensure that we are converging towards the best set of weights in the Genmatch function in R. I was reading the paper on ...
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27 views

R- trouble understanding how setting estimand to “ATE” is affecting matching in “Matching” package

I am working on a project where I am using observational data from patients and trying to find a causal relationship on how Treatment dose affects Patient recovery. Since the data is observational, I ...
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0answers
19 views

Logistic regression when only TRUE values are observed, but a control sample exists

I'm involved with a creel survey. We have reason to believe that anglers are keeping the larger fish they catch, or at least that a relationship exists between the size of caught fish and the ...
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0answers
13 views

Econometric Models in Economic Development Theory

I have been reading some Economic Development and Policy Research papers and I realise there is extensive employment of econometric tools and models. For example, one of the papers used an Oaxaca ...
4
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1answer
41 views

How to name a bias that is not quite the “immortality bias”

Strange question from me, but try to follow me. I do not remember or name correctly a type of bias in cohort study which is pretty clear in my mind. I try to explain: Let's assume that I want to test ...
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0answers
9 views

Estimating incidence on data with limited observation

I have a data of many individuals and wish to know whether a certain event occurred during a specific time frame with each one. The problem is that each individual was observed only a certain portion ...
0
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1answer
176 views

Conditional treatment effect and average treatment effect under no unmeasured confounders (ignorability)

The conditional treatment effect (CATE) is defined as: $$ \tau(x) = \mathbb{E} \left[ Y^1- Y^0 \mid X = x \right], $$ the average treatment effect (ATE) is defined as $$ \tau_{ATE} = \mathbb{E}\...
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1answer
45 views

Evaluating propensity score matches- what to do when ratio of variances or standardized means of difference go to infinity?

I am working on a project where I am comparing the effects of a particular treatment on patients with other patients who didn't receive the treatment. As I am trying to replicate a randomized ...
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1answer
39 views

How can I determine how often an event occurs based on collected data how long one has to wait for an occurence

This is an experiment I can only observe, not design/change. I make the following observations: A police officer frequently monitors the same traffic location in the same manner. I see the officer ...
4
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2answers
731 views

In propensity score matching, should a variable used in exact matching also be used in the model?

In propensity score matching, we can match on variables exactly. For example, we can match males with other males only. Additionally, the variable can be specified in the model. Here's some SAS code ...
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0answers
26 views

Model mean/median change per observation time?

A Cox proportional hazards model makes it possible to investigate how an independent variable affects the risk of a dichotomous state occurring per observation time. Is it possible to model (A Cox ...
2
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1answer
119 views

Why fixed design analysis for observational data [duplicate]

Why do we use a fixed design analysis of regression coefficients, even for observational data, where the design is not fixed? For instance: $Var[\hat \beta]=(X'X)^{-1}\sigma^2$ is conditional on $X$. ...
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2answers
59 views

Selecting the control group in a before-after study

I am interested in analyzing the effect of a specific change in traffic conditions on the amount of road accidents in a city. I need to select a comparison group; my approach is to select from ...
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0answers
106 views

Prospective studies and variable updates: level of evidence

In a cohort study, I'm measuring the apparition of a disease over time and confronting it against an exposition variable, which we'll call X. This is a very straight-forward analysis where I have ...
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0answers
22 views

Matching inflation

I have data on a few millions of patients, about 1000 of them are cases, that is, they were diagnosed having a certain disease at some timepoint in their life. I think I basically have two options: 1)...
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1answer
731 views

Cox Proportional and Pooled logistic regression in a observational cohort study - laymans terms

So my brain is just not understanding the difference between the two above. I am currently writing a literature review and have to explain the significance of what was found in the research. The ...
0
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1answer
13 views

Independence of time intervals in ANOVA?

I am not sure how the independence assumption in ANOVA applies in this scenario... We have observational data on the foraging depth of whales across the summer separated into time intervals. We want ...
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0answers
28 views

case-control study with cross-sectional data

I have a General Practitioner dataset for several thousand patients, taken at a single snapshot in time (let's call it time X). Patients that have died since the database was set up are therefore not ...
2
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0answers
44 views

How to combine observational studies

I am trying to show the releationship between a drug and an outcome in a particular setting. Using a systematic review, I have found 18 studies addressing this topic. Among those, the highest quality ...
2
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2answers
56 views

Differences in potential explanations between observational and experimental studies

Imagine we have a categorical variable, A—for example, whether somebody owns a dog or not—and a quantitative variable, B—for example, how many days a person is sick in a given year. ...
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1answer
218 views

How to reason about causal effect in time series when the treatment group reacts even before treatment?

Context: I'm running into a strange phenomenon about treatment effect and causality that I'll try to recreate here. Let's say I'm doing an observational study: Do people spend more time online as a ...
2
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1answer
665 views

Difference between using propensity score matching and CausalImpact for causal inference?

I'm investigating causal effect in some financial data, and I'm using two different approaches: propensity score matching with stratification and the CausalImpact package for Bayesian structural time ...
3
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3answers
585 views

What's the standard terminology for variables in observational studies vs experiments?

My stats textbook (De Veaux et al., 2008) advises using the terms response variable and predictor/explanatory variable in observational studies vs response variable and factor in experiments. However, ...
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1answer
91 views

Less than half of medical procedures are based on adequate evidence. What percent of those should we expect to be wrong?

"The proportion of medical procedures unsupported by evidence may be nearly half." If we assume that half of all procedures are based on observational data, what methods can we use to estimate how ...