Questions tagged [epidemiology]

Epidemiology is the study of the distribution and spread of disease or illness at the population level.

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Relationship between sensitiviy, probability of detection and Prevalence

Folks, I have 3 questions: If I know the number of exams performed with a specific test on a group of patients and the test's sensitivity, can I directly estimate the overall probability of detecting ...
1 vote
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Sample Size: Cluster Randomized Trials

I seek a peer check on my approach in calculating the sample size for pair-matched or stratified cluster randomized trials assuming 80% power. Some background on the study: I am working with ...
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Survival analysis: usage of local control and local recurrence free survival [closed]

I noticed that in some publications the terms "local control" and "local recurrence free survival" are used interchangeably, in others the local control does not include the death ...
27 views

Calculating death rates for an increasing population over the long-term

I'm part of a small long-term outcomes study for a specific MH intervention. We're becoming a little alarmed at the number of subjects who seem to have died in their 20s and we'd like to make sure ...
1 vote
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What standard population to use in my epidemiological study?

I need to standardized my mortality rations. for the period 2000-2022 in one European country. However, I am not use what standard population to use? Is Sagi outdated? In addition, I find this ...
1 vote
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penalized package [closed]

Has anyone used penalized package? I was using it for lasso in Cox regression, with time-varying coefficients. The problem is when I made a plot with ...
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1 vote
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Is this non-mathematical interpretation of cause-specific vs subdistribution hazards sensible?

I am interested in estimating the risk of readmissions accounting for the competing risk of death. I would like to explain both types of models to people with a basic understanding of statistics. ...
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27 views

Sample size for a vector of proportions and simulation

Currently, there are more than 10 variants of omicron virus. Say, variant proportions are X1=0.1, X2=0.35, X3=0.15, etc. I need to calculate the number of samples needed to detect the proportion of ...
11 views

How to deal with exposure status change and outcome contribution in different exposure status?

I want to estimate the risk of cardiovascular events in patients with diabetes (exposed group) compared to patients without diabetes (unexposed group). How do we deal (in the analysis) with patients ...
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Variability of patients in different Hospitals

just to let you know that my statistical background is not very good. I made funnel graphs which shows the effect of polypharmacy against practice size. In the funnel graphs, a dot presents a single ...
1 vote
79 views

Incidence rates from manual calculation differs from that obtained from the estimated marginal means of a poisson regression

Poisson Regression I have done a poisson regression where the data is individual-level data, the dependent variable, event is 1 if individual had the event or 0 if ...
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How to perform conditional poisson regression for a 1:5 matched cohort study?

I have a matched cohort population using data that spans the years 2016-2021. My exposure of interest is continuous dialysis treatment, and my outcome is e.coli infections (count outcome). Each time ...
23 views

Proportion mediated possible for Binary outcome, Continuous mediator?

I am running a mediation analysis on a categorical X (race/ethnicity), binary Y (disease status), and ordinal M (can be any integer 0 - 10). N-controls = 1321. Ncases = 384. I conducted this analysis ...
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Interpreting Poisson GAM for epidemiological model

I'm working on a project where I investigate the relationship between PM2.5 (a form of pollution) and ischemic stroke hospitalization (i.e. number of hospitalizations total, collected per day). My ...
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1 vote
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Region of Practical Equivalence (ROPE)

I seek to understand how to employ the Region of Practical Equivalence (ROPE), so I conducted a basic Bayesian analysis of disease incidence rates on a public data set. Is my rationale sound regarding ...
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Statistical tests for two rates

For a paper I am writing, I am comparing influenza burden in two locations. For each location, I have the rate of symptomatic influenza infections per 100,000 population, as well as a 95% confidence ...
1 vote
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How to construct a common control group in two cohorts with different disease outcomes?

Question details: I have cohort data with a total of 100,000 participants. For some reason, I need to select 2000 participants as controls to construct a control group. I have 3,000 cases of disease A ...
70 views

Difference-in-Differences with Multiple Time Periods: 'Always treated' group?

The title of the post refers to this paper by Callaway & Sant'Anna: https://www.sciencedirect.com/science/article/pii/S0304407620303948?via%3Dihub Let us assume that I have data on incidence ratio ...
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Difference between Cross-Sectional and Nested Case-Control Samples in Cohort Studies

I have a question regarding the cross-sectional sample from the most recent visit and the nested case-control sample extracted from a cohort study, especially when the exposure of interest was ...
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1 vote
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Statistical models for simultaneous study designs

I have thinking about a problem that can be encountered in environmental epidemiology, but I guess in other research fields too. Background: In environmental epidemiology the interest is mostly to ...
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Association of soil toxic element with epigenetic aging in four different cities

I would like to do regression analysis (linear/non-linear) using gam models for soil toxic elements and epigenetic age acceleration; here, we have measured soil elements (mg/kg) using ICP-MS in four ...
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Clustering and segmented regression interrupted time series analysis

I would like to perform an interrupted time series analysis to look at the impact of the pandemic on cancer incidence using individual level data. I plan to use a negative binomial segmented ...
112 views

Applying logistic regression to data recorded on a 0-10 scale

I used 0-10 scale to record disease data on each plant. 0 = no disease 1 = 1–10% of plant leaves infected 2 = 11–20% of plant use infected . . . 10 = 91–100% of ...
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Cox model: exclusion of certain subjects at known times

Background We are performing a register based cohort study analysing the effect of influenza exposure (no/yes) on time to event in pregnancy. Exposure period is any time during first trimester. ...
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What will be the sample size to determine the incidence and prevalence when estimated prevalence is 17.93 per 100000?

I want to conduct a study to determine the incidence and prevalence of oral cancer in an area. I prefer door to door community based screening by Oral visual examination and refer suspected case for ...
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C-statistic with censoring data

I have analyzed a cancer dataset that contains risk factors and an outcome. However, I am dealing with many observations lost to follow-up and missing values.   I want to obtain the c-statistic, but I ...
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Interpretation of values of survival analysis

I am looking for some input regarding the interpretation of a survival analysis with the survfit()-function. A bit about my data: I am interested in analyzing in R whether people with a specific level ...
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How can we get the calibration plot for Cox regression?

The calibration plot for logistic regression is quite intuitive for me because we can directly get the predicted probability. However, in Cox regression model we just get the hazard ratio so how can ...
35 views

Difference between Mortality Rate, Crude Death Rate and Cause-Specific Death Rate

Like the title explains, I'm having a difficulty understanding the differences between: Mortality Rate Crude Death Rate Cause-Specific Death Rate. Somebody please explain the differences.
1 vote
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Time being a mediator of sort but planned on used time varying cox ph model?

I am working on a project where literature has traditionally treated the exposure as a time-dependent exposure and used a time varying cox ph model. During the logistic, and normal cox PH analysis ...
225 views

CoxPH with one ID contributing many comparator observations

UPDATE----------------- I have data where one ID can serve as a comparator several times. This is done by creating a variable to group the treated in variable GROUP....
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1 vote
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Medication switching in pregnancy

My study design seeks to answer the following question: What are the potential risks of switching medications from pre-pregnancy to pregnancy for (1) individuals who switch from medication A to B; (2) ...
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Strange interaction term estimate in a logistic regression with a large class imbalance between exposure groups. How to interpret?

EDIT 2 In reply to one of the commenters, here is the 2x2x2 table. Y = 1 : Y = 0. X = 1 X = 0 M = 1 9 : 73 3 : 29 M = 0 34 : 245 1,214 : 21,204 EDIT 1 In my attempts to make things simpler when ...
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Survival analysis vs Cumulative incidence vc Incidence rate for cohort with varying baseline dates

Research question: I am interested in analyzing in R whether people with a specific level (out of four levels) of a blood parameter BP have a higher risk for developing a specific disease D. A ...
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How do you convert hazard ratios to differences in life expectancy?

How do epidemiologists convert hazard ratios to difference in life expectancy? For example, let's say I find that the hazard ratio of all-cause mortality in City A is 1.25 compared to City B. I want ...
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Do I need to care if an adjustment variable violates the proportional hazards assumption?

I'm assessing the effect of an exposure variable on cancer risk. I am not necessarily trying to build the model that best predicts cancer risk, I am instead trying to best isolate the effect on cancer ...
1 vote
651 views

Calculate incidence density/ rate after weighting

How to calculate an incidence density/ rate for weighted data, e.g. using weighting methods such as matching weights, IPW, ...? -- UPDATE 06.11.2023: Regard the following paper as an example of ...
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How can I apply McNemar’s test in matched case control study on SPSS?

When conducting a case-control study with 120 cases 1:1 to 120 controls and examining whether they had a binary exposure prior to developing the disease. I am using conditional logistic regression for ...
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After obtaining a minimally sufficient set from a DAG, which variables should I include in the logistic regression model?

I have created a DAG using daggity, and from this DAG, two variables need to be controlled to evaluate the unbiased total effect of the exposure on the outcome. However, I'm confused about whether I ...
1 vote
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Causal mediation analysis for time to event endpoints in randomized controlled trial data analysiscausal inference survival-analysis

I am struggling with a situation. I have an RCT where there is an intermediate variable and an ultimate endpoint of survival (a time to event endpoint). I want to establish that the intermediate ...
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I have some epidemiological data, relating to the prevalence of obesity at UK local authority level. For the purpose of exploration I want to derive the median obesity prevalence. However, I need to ...
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Converting incidence of new diagnoses to DALYs, or vice-versa

A recent Nature Medicine study looked at new diagnoses of a wide range conditions from electronic health records, for both a group with a particular exposure (here, Covid infection) and an unexposed ...
1 vote
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What type of bias is this?

I have a longitudinal cohort study, with individuals that diagnosed with Disease A at "start", and they all developed Complication B at "end" in my study period (my study period ...
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Why marginal odds in frequency matched case-control?

Let $D$ denote sampling with $D=1$ indicating subject being sampled and $D=0$ otherwise. $W$ denotes intrinsic variable of subjects, $X$ denotes exposure of interest and $Y$ denotes the binary outcome....
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1 vote
134 views

Different results with splitting data vs. adjusting

I have a question regarding the results that I have achieved from my analysis. I'm new to statistics and the understanding of epidemiology. Please, help me interpret this better. I know what a ...
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Difference between query and distribution in causal inference

Reading the causality literature, we see the concepts of "interventional" and "counterfactual" query as well as "interventional" and "counterfactual" ...
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Is it valid to predict excess deaths on data used to fit a Poisson regression model?

I skimmed through a study: Excess Death Rates for Republican and Democratic Registered Voters in Florida and Ohio During the COVID-19 Pandemic that estimates excess death rates of Democrats and ...
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1 vote
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How to deal with participants recruited twice in a RDS (repondent-driven sampling) study?

I have RDS data and identified participants recruited twice during the study. How should I handle these duplicates? If I delete the second recruitment, it will disrupt the network. Can I consider the ...