2015
DOI: 10.1007/s11999-015-4239-4
|View full text |Cite
|
Sign up to set email alerts
|

Statistics in Brief: An Introduction to the Use of Propensity Scores

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
58
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
6
1

Relationship

0
7

Authors

Journals

citations
Cited by 70 publications
(58 citation statements)
references
References 29 publications
(19 reference statements)
0
58
0
Order By: Relevance
“…Propensity score matching was used to minimize the effects of confounding related to differences in patient demographics as a result of the nonrandom assignment of patients to outpatient or inpatient surgery. This type of matching uses a propensity score, which is a single score that is calculated based on covariate data, to match patients from different treatment groups [18]. In the current study, each ''outpatient'' and ''LOS = 0'' case was matched with one ''inpatient'' and ''LOS [ 0'' case, respectively, without replacement with regard to gender, body mass index, modified CCI, functional status before surgery, and smoking status.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…Propensity score matching was used to minimize the effects of confounding related to differences in patient demographics as a result of the nonrandom assignment of patients to outpatient or inpatient surgery. This type of matching uses a propensity score, which is a single score that is calculated based on covariate data, to match patients from different treatment groups [18]. In the current study, each ''outpatient'' and ''LOS = 0'' case was matched with one ''inpatient'' and ''LOS [ 0'' case, respectively, without replacement with regard to gender, body mass index, modified CCI, functional status before surgery, and smoking status.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…URL https://www.r-project.org/). For the propensity score matching analysis, a 1:1 match was performed (control group) [14], using the administration of the DAC as the dependent variable and the age, gender, body mass index (BMI), PJI risk score, CCI, length of stay, and operative time as response variables. The match was performed by using the optimal matching method, where the absolute average distance between all matched pairs is minimized.…”
Section: Discussionmentioning
confidence: 99%
“…The sample consisted of a total of 177 subjects. All the patients who underwent local antibioticprophylaxis treatment with the antibiotic hydrogel (antibiotic loaded hydrogel group, ALH) (N = 17) were compared with a 1:1 ratio to the patients selected through the propensity score matching [14] (control group).…”
Section: Study Design and Populationmentioning
confidence: 99%
See 1 more Smart Citation
“…This method made similar baseline characteristics between two groups in order to create "quasi-random experiment" from retrospective data (9,10). Using a multivariable logistic regression model, we calculated the propensity scores in terms of clinicopathological characteristics (covariates: age, gender, tumor location, tumor grade, T stage, N stage and pathological stage).…”
Section: Propensity Score Matching (Psm)mentioning
confidence: 99%