Frequencies for masanctioned2019 dataset : by Jean Roth , jroth@nber.org , 15 Feb 2019 Frequencies for state variable in masanctioned2019 dataset : State | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for county variable in masanctioned2019 dataset : County | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for organizationname variable in masanctioned2019 dataset : Organizatio | n Name | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for planname variable in masanctioned2019 dataset : Plan Name | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for typeofmedicarehealthplan variable in masanctioned2019 dataset : Type of | Medicare | Health Plan | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for monthlyconsolidatedpremiumi variable in masanctioned2019 dataset : Monthly | Consolidate | d Premium | (Includes | Part C + D) | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for annualdrugdeductible variable in masanctioned2019 dataset : Annual Drug | Deductible | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for drugbenefittype variable in masanctioned2019 dataset : Drug | Benefit | Type | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for typeofadditionalcoverageoff variable in masanctioned2019 dataset : Type of | Additional | Coverage | Offered in | the Gap | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for drugbenefittypedetail variable in masanctioned2019 dataset : Drug | Benefit | Type Detail | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for contractid variable in masanctioned2019 dataset : Contract ID | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for planid variable in masanctioned2019 dataset : Plan ID | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for segmentid variable in masanctioned2019 dataset : Segment ID | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for innetworkmoopamount variable in masanctioned2019 dataset : In-network | MOOP Amount | ** | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for overallstarrating variable in masanctioned2019 dataset : Overall | Star Rating | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 Frequencies for overallstarratingstr variable in masanctioned2019 dataset : Overall | Star Rating | Freq. Percent Cum. ------------+----------------------------------- . | 1 100.00 100.00 ------------+----------------------------------- Total | 1 100.00 by Jean Roth , jroth@nber.org , 15 Feb 2019