Questions tagged [observational-study]
An observational study involves purely observing the state of the world without manipulating it.
134
questions
7
votes
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 ...
0
votes
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 ...
0
votes
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
votes
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. ...
0
votes
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 ?
1
vote
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
votes
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 ...
1
vote
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
votes
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 ...
1
vote
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
votes
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 ...
0
votes
0answers
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
votes
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 ...
1
vote
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 ...
0
votes
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 ...
1
vote
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 ...
0
votes
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 ...
1
vote
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
votes
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
...
1
vote
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 ...
1
vote
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
votes
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 ...
1
vote
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
votes
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 ...
0
votes
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 ...
0
votes
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 ...
0
votes
0answers
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 ...
0
votes
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 ...
0
votes
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
votes
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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vote
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
votes
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}\...
1
vote
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 ...
0
votes
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
votes
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 ...
0
votes
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
votes
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 $X$. ...
1
vote
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 ...
0
votes
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 ...
1
vote
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)...
1
vote
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
votes
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 ...
1
vote
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
votes
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
votes
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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vote
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
votes
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
votes
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, ...
0
votes
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 ...
