Figure 1 - Risk and utility, by data synthesis method and overall treatment rate
Figure 2 - Doctoral scientists and engineers with no employment sector changes from 2015 to 2019, by demographic and degree characteristics: Comparison of original data, sequential hotdeck synthetic data, and MACH synthetic data 
Table 1 - Source of raking variables
Table 2 - Risk strata resulting from matching exercise 
Table 3 - Treatment rate scenarios, by risk strata
Table 4 - LSDR 2015–19 cases that are uniquely and correctly matched to all three CS-PUFs, by data synthesis method and overall treatment rate
Table 5 - Rankings of synthetic data approaches, by utility measure
Table 6 - Ratio of utility measures between each synthetic approach to the imputation approach
Table 7 - Key features of the three data synthesis methods 
Table 8 - Distribution of LSDR 2015–19 cases by number of CS-PUFs matched uniquely and correctly
Table 9 - Distribution of cases, by the number of variables with changes
Table 10 - Pairwise correlations using the original data and synthetic data
Table A-1 - Variable list
