In this paper, we propose a change-point mixed model to assess the change in the trend of outpatient antibiotic use in a Bayesian framework, where the change-points are unknown parameters of the model. Model selection using DIC indicates that the data supports the model with a country-specific change-point. The location of the change-points may be related to points in time where public health strategies aiming at increasing the awareness of the public to a more rational use of antibiotics or targeting to reduce overconsumption of antibiotics were initiated.
AdriaenssensNCoenenSVersportenAMullerAFaesCVankerckhovenVAertsMHensNMolenberghsGGoossensH (on behalf of the ESAC Project Group) (2011) European Surveillance of Antimicrobial Consumption (ESAC): outpatient antibiotic use in Europe (1997–2009). Journal of Antimicrobial Chemotherapy, 66Suppl. 6, vi3–vi12.
2.
CarlinBPGelfandAESmithAFM (1992) Hierarchical Bayesian analysis of change points problems. Journal of the Royal Statistical Society. Series C (Applied Statistics), 41, 389–405.
3.
CasellaGGirónFJMartínezMLMorenoE (2009) Consistency of Bayesian procedures for variable selection. The Annals of Statistics, 37, 1207–28.
4.
CoenenSAdriaenssensNVersportenAMullerAMinaluGFaesCVankerckhovenVAertsMHensNMolenberghsGGoossensH; ESAC Project Group (2011) European Surveillance of Antimicrobial Consumption (ESAC): outpatient use of tetracyclines, sulphonamides and trimethoprim, and other antibacterials use in Europe (1997–2009). Journal of Antimicrobial Chemotherapy, 66Suppl. 6, vi57–vi70.
5.
DaveyPFerechMAnsariFMullerAGoossensH (2008) Outpatient antibiotic use in the four administrations of the UK: cross-sectional and longitudinal analysis. Journal of Antimicrobial Chemotherapy, 62, 1441–47.
6.
DominicusARipattiSPedersenNLPalmgrenJ (2008) A random change-point model for assessing variability in repeated measures of cognitive function. Statistics in Medicine, 27, 5786–98.
GhoshPVaidaF (2007) Random changepoint modelling of HIV immunologic responses. Statistics in Medicine, 26, 2074–87.
9.
GoossensHFerechMVander SticheleRHElseviersM (2005) Outpatient antibiotic use in Europe and association with resistance: a crossnational database study. Lancet, 365, 579–87.
10.
HallCBLiptonRBSliwinskiMStewartWF (2000) A change-point model for estimating the onset of cognitive decline in preclinical Alzheimer’s disease. Statistics in Medicine, 19, 1511–66.
11.
HallCBYingJKuoLLiptonRB (2003) Bayesian and profile likelihood change-point methods for modeling cognitive function over time. Computational Statistics & Data Analysis, 42, 91–109.
12.
HensNKvitkovicovaAAertsMHlubinkaDBeutelsP (2010) Modelling distortions in seroprevalence data using change-point fractional polynomials. Statistical Modelling, 10(2), 159–75.
13.
HuttnerBGoossensHVerheijTHarbarthS (2010) Characteristics and outcomes of public campaigns aimed at improving the use of antibiotics in outpatients in high-income countries. The Lancet Infectious Diseases, 10(1), 17–31.
14.
Jacqmin-GaddaHCommengesDDartiguesJ (2006) Random changepoint model for joint modeling of cognitive decline and dementia. Biometrics, 62, 254–60.
15.
KiuchiASHartiganJAHolfordTRRubinsteinPStevensCE (1995) Change-points in the series of T4 counts prior to AIDS. Biometrics, 51, 236–48.
16.
LangeNCarlinBPGelfandAE (1992) Hierarchical bayes models for the progression of HIV infection using longitudinal CD4 T-cell numbers (with discussion). Journal of American Statistical Association, 87, 615–32.
17.
LindleyDV (1957) A statistical paradox. Biometrika, 44, 187–92.
18.
MinaluGAertsMCoenenSVersportenA. (2011) Application of mixed-effects models to study the country-specific outpatient antibiotic use in Europe: a tutorial on longitudinal data analysis. Journal of Antimicrobial Chemotherapy, 66Suppl. 6, vi79–vi87.
19.
MuggeoVMR (2003) Estimating regression models with unknown break-points. Statistics in Medicine, 22, 3055–71.
20.
MulderJKlugkistIvan de SchootRMeeusWHJSelfhoutMHoijtinkH (2009) Bayesian model selection of informative hypotheses for repeated measurements. Journal of Mathematical Psychology, 53, 530–46.
21.
NtzoufrasI (2009) Bayesian modeling using WinBUGS. New York: John Wiley & Sons.
22.
OverstallAMForsterJJ (2010) Default Bayesian model determination methods for generalized mixed models. Computational Statistics and Data Analysis, 54, 3269–88.
23.
PastorRGuallarE (1998) Use of two-segmented logistic regression to estimate change-points in epidemiologic studies. American Journal of Epidemiology, 148(7), 631–42.
24.
PlummerM (2008) Penalized loss functions for Bayesian model comparison. Biostatistics, 9(3), 523–39.
25.
SlateEHTurnbullBW (2000) Statistical models for longitudinal biomarkers of disease onset. Statistics in Medicine, 19, 617–37.
26.
SmithAFM (1975) A Bayesian approach to inference about a change-point in a sequence of random variables. Biometrika. 62, 407–16.
27.
SpiegelhalterDJBestNGCarlinBPLindeA (2002) Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society, Series B, 64(4), 583–639.
28.
SturtzSLiggesUGelmanA (2005) R2WinBUGS: A Package for Running WinBUGS from R. Journal of Statistical Software, 12(3), 1–16.
