Questions tagged [observational-study]

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

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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 ...
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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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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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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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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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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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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 ...
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62 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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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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19 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 ...
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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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60 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 ...
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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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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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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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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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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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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 ...
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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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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 ...
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112 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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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 ...
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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, ...
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25 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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38 views

Double Mendelian Randomization: Reasonableness & False Positive Concerns

I've been interested in mendelian randomizations (a form of instrument variable analyses) as a method for gaining insight into causal relationships between risk factors and outcomes. An example i ...
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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 ...
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Evaluating Impact of Unobserved Confounders - Is the E-Value applicable for Non-Significant Group Differences?

I have conducted an analysis of treatment effects based on observational data (via statistical matching). As suggested by VanderWeele and Ding (2017), I want to evaluate the sensitivity of my analysis ...
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560 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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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 ...
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96 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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53 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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103 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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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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510 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 ...
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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 ...
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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 ...
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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 ...
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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. ...
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183 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 ...
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533 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 ...
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464 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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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 ...
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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 ...
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254 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 ...
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76 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" ...
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767 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 ...
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165 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 ...
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25 views

Unmeasured covariate adjustment

A study was presented where the authors used multivariable logistic regression to assess association between a risk factor and an incident disease outcome. The association was statistically ...
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Why is Average Treatment Effect different from Average Treatment effect on the Treated?

In RCTs, randomisation balances unmeasured confounders and, I'm told, ATE and ATT would be the same. In observational studies, this is not possible and Propensity Scores are used in various ways to ...
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118 views

Meta analysis of one-armed observational studies with varying follow up (time)?

I am about to start a meta analysis investigating the retention of different dental fissure sealers. Data extracted from the studies are: (number of teeth completely sealed at the end of study) (...