Questions tagged [observational-study]
An observational study involves purely observing the state of the world without manipulating it.
129
questions
1
vote
1answer
27 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
43 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
51 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?
0
votes
1answer
56 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
27 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 ...
3
votes
3answers
70 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
26 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
32 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
30 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
25 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 ...
1
vote
1answer
87 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
25 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
21 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
28 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
66 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
155 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
35 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
21 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
12 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 ...
1
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
134 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}\...
0
votes
0answers
56 views
Cohort Study Sample Size and Multiple Comparisons
I'm designing an epidemiological retrospective cohort study with a large number of exposures and outcomes, and I'm trying to figure out how many subjects I'll need in order to run all my analyses. The ...
0
votes
0answers
85 views
Inference from regression in presence of multicolinearity
I would like to estimate the effect of one independent variable on the predicted variable in the purely observational study. On the other hand I know that there exists another independent variable, ...
1
vote
1answer
31 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
28 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
624 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
106 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
56 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
105 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
21 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)...
2
votes
1answer
575 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
11 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
27 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
39 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
53 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. ...
1
vote
1answer
197 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 ...
1
vote
1answer
578 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
522 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 ...
1
vote
0answers
20 views
Selecting controls from a case-cohort study when location is important
I am looking at the causes of a disease in cows, both 'environmental' (ie ground-drainage, bedding type etc) and 'biological' (previous disease, sex, weight etc). Most environmental variables are the ...
5
votes
1answer
258 views
What are the problems with number needed to treat (or harm) in observational studies?
I have been asked to comment on the use of NNT (number needed to treat) and NNH (number needed to harm) in observational studies. My intuition doesn't give me any reasons these would be problematic ...
0
votes
1answer
86 views
Post-Match Analysis After Already Adjusting For Everything
Let's say I am conducting an observational study in which a group that received treatment (T+) is matched to another group (T-) using propensity score analysis where I use the "throw-the-kitchen-sink" ...
1
vote
1answer
827 views
Adjusting Sample with Propensity Score Weighting and ATT
I have a retrospective sample that contains a treatment and non-treatment group with >10 covariates comprised of both categorical and continuous variables. I used the chi-squared and Mann-Whitney U ...
1
vote
0answers
174 views
How to implement a Poisson Gamma model to predict study recruitment?
After researching there are a lot of papers that suggest study recruitment can be modeled after a Poisson Gamma distribution. (which might just be a negative binomial distribution?) They also have a ...
