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Table 2 Summary of the analyses for the dependent variable Access (PREM), multilevel linear regression

From: Case-mix adjustments for patient reported experience and outcome measures in primary care: an empirical approach to identify patient characteristics as case-mix adjusters based on a secondary analysis of an international survey among patients and their general practitioners in 34 countries

Potential case-mix variable

Fixed effect significant (y/n)

Slope effect

GP level important* (y/n)

Slope effect

Country level important (y/n)

Case-mix control (y/n)

Self-reported general health

Yes

Worse self-reported health → worse experienced access

No

No

Yes

Longstanding disease

No

No

No

No

Patient’s age

Yes

Older than 40 → better experienced access

No

No

Yes

Patient’s sex

No

No

No

No

Education

Yes

Higher education → better experienced access

No

No

Yes

Income

Yes

Higher income → better experienced access

No

No

Yes

Migrant status

Yes

Migrant status → lower experienced access

No

No

Yes

Place of living

Yes

Outside big cities → better experienced access

Yes

No

No

Importantly more variation big (inner) cities compared to rural areas

  1. *Important means that the difference in variance between categories is more that 0.25*variance in the model with fixed effect and random intercept