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        Models for Count Data With an Application to Healthy Days Measures: Are You Driving in Screws With a Hammer?

        No. of Mentally Unhealthy DaysObservedLinearPoisson
        066.781.378.06
        13.543.3716.04
        25.897.2518.53
        33.0720.0916.48
        41.5124.7412.66
        53.5115.558.99
        60.3811.536.16
        71.217.494.19
        80.285.172.86
        90.062.591.97
        102.780.671.36
        110.010.200.93
        120.230.63
        130.010.42
        140.390.27
        152.750.17
        160.010.10
        170.000.06
        180.010.04
        190.000.02
        201.570.01
        210.070.01
        220.020.00
        230.020.00
        240.010.00
        250.450.00
        260.090.00
        270.090.00
        280.110.00
        290.110.00
        305.020.00

        Figure 1. Comparison of the observed percentage distribution of number of mentally unhealthy days and the percentage distribution predicted by the multivariate linear and Poisson regression models. Data were obtained from the 2009 Behavioral Risk Factor Surveillance System in 12 states.

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        No. of Mentally Unhealthy DaysObservedNegative BinomialZero-Inflated Negative Binomial
        066.7865.5268.22
        13.548.384.06
        25.894.523.16
        33.073.062.61
        41.512.282.22
        53.511.801.92
        60.381.471.67
        71.211.231.48
        80.281.041.31
        90.060.901.17
        102.780.791.04
        110.010.690.94
        120.230.620.84
        130.010.550.76
        140.390.490.69
        152.750.450.63
        160.010.400.57
        170.000.370.52
        180.010.340.47
        190.000.310.43
        201.570.280.39
        210.070.260.36
        220.020.240.33
        230.020.220.30
        240.010.210.28
        250.450.190.26
        260.090.180.24
        270.090.170.22
        280.110.150.20
        290.110.140.19
        305.020.130.17

        Figure 2. Comparison of the observed percentage distribution of number of mentally unhealthy days and the percentage distribution predicted by the negative binomial and zero-inflated negative binomial models. Data were obtained from the 2009 Behavioral Risk Factor Surveillance System in 12 states.

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