Are healthy patients an appropriate control group?How to select a control / comparison group?How to analyze...
Is there a way to find out the age of climbing ropes?
A bug in Excel? Conditional formatting for marking duplicates also highlights unique value
Too soon for a plot twist?
Called into a meeting and told we are being made redundant (laid off) and "not to share outside". Can I tell my partner?
Why do we call complex numbers “numbers” but we don’t consider 2 vectors numbers?
PTIJ: Aliyot for the deceased
Quitting employee has privileged access to critical information
Why would /etc/passwd be used every time someone executes `ls -l` command?
Error in TransformedField
Custom javascript not working
Should we avoid writing fiction about historical events without extensive research?
What is the purpose of a disclaimer like "this is not legal advice"?
Why are special aircraft used for the carriers in the United States Navy?
Questions of the type "What do you think other people would think?"
How do we objectively assess if a dialogue sounds unnatural or cringy?
Is there such a thing in math the inverse of a sequence?
Why do phishing e-mails use faked e-mail addresses instead of the real one?
Why would the IRS ask for birth certificates or even audit a small tax return?
“I had a flat in the centre of town, but I didn’t like living there, so …”
Do natural melee weapons (from racial traits) trigger Improved Divine Smite?
Is divide-by-zero a security vulnerability?
Align equations with text before one of them
What is a term for a function that when called repeatedly, has the same effect as calling once?
Short story about an infectious indestructible metal bar?
Are healthy patients an appropriate control group?
How to select a control / comparison group?How to analyze this pre-post control-intervention data set?Determining minimum required sample size for control (for purposes of measuring lift)Control group construction in Synthetic Control MethodDynamic treatment timing in a panel-DiD frameworkAnalysis of pre-post treatment data with changes over timeanalytical methods for crossover study that has an addition control groupStatistical test to use?Making a control group out of a linear combination of possible control groupsControl group selection
$begingroup$
I am working on a study where patients with a chronic disease received a treatment. The goal is to determine the effect of the treatment on various outcome variables. I have pre and post data (before and after the treatment) for the sick patients and also for a control group of patients who are healthy. It would have been considered unethical to withhold treatment from sick patients, hence there was no control group of sick patients who did not receive the treatment.
I plan to analyze the data using linear mixed effects models. I’ve seen examples of how to analyze this type of data when you have pre/post data with a control group, for example including variables in the model such as the time point, whether the individual is in the treatment or control group, and the interaction between the two.
However, I’m wondering about the appropriateness of this approach when the control group is healthy patients. Does it really make sense to make comparisons to a healthy group in this way when the goal of the study is to determine what effect the treatment had? By making comparisons to a group of healthy patients, is this answering a different question?
Appreciate any comments. thank you!
control-group treatment
$endgroup$
add a comment |
$begingroup$
I am working on a study where patients with a chronic disease received a treatment. The goal is to determine the effect of the treatment on various outcome variables. I have pre and post data (before and after the treatment) for the sick patients and also for a control group of patients who are healthy. It would have been considered unethical to withhold treatment from sick patients, hence there was no control group of sick patients who did not receive the treatment.
I plan to analyze the data using linear mixed effects models. I’ve seen examples of how to analyze this type of data when you have pre/post data with a control group, for example including variables in the model such as the time point, whether the individual is in the treatment or control group, and the interaction between the two.
However, I’m wondering about the appropriateness of this approach when the control group is healthy patients. Does it really make sense to make comparisons to a healthy group in this way when the goal of the study is to determine what effect the treatment had? By making comparisons to a group of healthy patients, is this answering a different question?
Appreciate any comments. thank you!
control-group treatment
$endgroup$
add a comment |
$begingroup$
I am working on a study where patients with a chronic disease received a treatment. The goal is to determine the effect of the treatment on various outcome variables. I have pre and post data (before and after the treatment) for the sick patients and also for a control group of patients who are healthy. It would have been considered unethical to withhold treatment from sick patients, hence there was no control group of sick patients who did not receive the treatment.
I plan to analyze the data using linear mixed effects models. I’ve seen examples of how to analyze this type of data when you have pre/post data with a control group, for example including variables in the model such as the time point, whether the individual is in the treatment or control group, and the interaction between the two.
However, I’m wondering about the appropriateness of this approach when the control group is healthy patients. Does it really make sense to make comparisons to a healthy group in this way when the goal of the study is to determine what effect the treatment had? By making comparisons to a group of healthy patients, is this answering a different question?
Appreciate any comments. thank you!
control-group treatment
$endgroup$
I am working on a study where patients with a chronic disease received a treatment. The goal is to determine the effect of the treatment on various outcome variables. I have pre and post data (before and after the treatment) for the sick patients and also for a control group of patients who are healthy. It would have been considered unethical to withhold treatment from sick patients, hence there was no control group of sick patients who did not receive the treatment.
I plan to analyze the data using linear mixed effects models. I’ve seen examples of how to analyze this type of data when you have pre/post data with a control group, for example including variables in the model such as the time point, whether the individual is in the treatment or control group, and the interaction between the two.
However, I’m wondering about the appropriateness of this approach when the control group is healthy patients. Does it really make sense to make comparisons to a healthy group in this way when the goal of the study is to determine what effect the treatment had? By making comparisons to a group of healthy patients, is this answering a different question?
Appreciate any comments. thank you!
control-group treatment
control-group treatment
asked 4 hours ago
LauraLaura
163
163
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
This makes no sense to do because the average outcome of the healthy patients is meant to stand in for the average outcome of the sick patients had they not received treatment (which is not observed due to the fundamental problem of causal inference/unbearable lightness of being).
Without some additional strong assumptions, there is not much else you can do with this design. The difference-in-differences approach you outline above assumes that the sick when untreated share a trend with the healthy (though there may be a constant gap between them), which seems unlikely to hold.
$endgroup$
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "65"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstats.stackexchange.com%2fquestions%2f396288%2fare-healthy-patients-an-appropriate-control-group%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
This makes no sense to do because the average outcome of the healthy patients is meant to stand in for the average outcome of the sick patients had they not received treatment (which is not observed due to the fundamental problem of causal inference/unbearable lightness of being).
Without some additional strong assumptions, there is not much else you can do with this design. The difference-in-differences approach you outline above assumes that the sick when untreated share a trend with the healthy (though there may be a constant gap between them), which seems unlikely to hold.
$endgroup$
add a comment |
$begingroup$
This makes no sense to do because the average outcome of the healthy patients is meant to stand in for the average outcome of the sick patients had they not received treatment (which is not observed due to the fundamental problem of causal inference/unbearable lightness of being).
Without some additional strong assumptions, there is not much else you can do with this design. The difference-in-differences approach you outline above assumes that the sick when untreated share a trend with the healthy (though there may be a constant gap between them), which seems unlikely to hold.
$endgroup$
add a comment |
$begingroup$
This makes no sense to do because the average outcome of the healthy patients is meant to stand in for the average outcome of the sick patients had they not received treatment (which is not observed due to the fundamental problem of causal inference/unbearable lightness of being).
Without some additional strong assumptions, there is not much else you can do with this design. The difference-in-differences approach you outline above assumes that the sick when untreated share a trend with the healthy (though there may be a constant gap between them), which seems unlikely to hold.
$endgroup$
This makes no sense to do because the average outcome of the healthy patients is meant to stand in for the average outcome of the sick patients had they not received treatment (which is not observed due to the fundamental problem of causal inference/unbearable lightness of being).
Without some additional strong assumptions, there is not much else you can do with this design. The difference-in-differences approach you outline above assumes that the sick when untreated share a trend with the healthy (though there may be a constant gap between them), which seems unlikely to hold.
answered 3 hours ago
Dimitriy V. MasterovDimitriy V. Masterov
20.9k14094
20.9k14094
add a comment |
add a comment |
Thanks for contributing an answer to Cross Validated!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstats.stackexchange.com%2fquestions%2f396288%2fare-healthy-patients-an-appropriate-control-group%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown