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Table 3 Summary of results according different model specifications and estimation techniques—(Models M1 to M5)

From: Assessing real-world effectiveness of therapies: what is the impact of incretin-based treatments on hospital use for patients with type 2 diabetes?

    

Probability of being hospitalized

 

Length of hospital stay

    

Linear probability model

 

Zero truncated Poisson

    

Coeff (DID)

 

95%CI

 

IRR (DID)

 

95%CI

Changes in the matching variables:

M2

-0,02

 

-0,05

-

0,02

 

0,72

***

0,66

-

0,79

 

Socioeconomics: age, gender, partnership, employment situation, coverage eligibilty

            

Changes in the matching method:

            
 

Exact matching

M3

0,01

 

0,42

-

1,29

 

0,73

***

0,65

-

0,93

 

k-nearest (k = 5)

M4

-0,01

 

-0,04

-

0,01

 

0,74

***

0,69

-

0,79

Changes in the Two Part version model:

M5

    

0,82

***

0,74

-

0,91

 

Estimation of a ZIP model (results for the second part)

            
  1. Notes. Coeff = coefficient of the linear probability model; IRR = incidence rate ratios; 95%CI = 95% confidence intervals; The models are controlled for the full same set of covariates (see Table 3);*** p < 0.0001
  2. †Second part of the Hurdle model, i.e. the number of days hospitalized conditionally to at least one hospital admission