Table 4.

Correlations between income¹, cocaine-supply related², cocaine-purchasing³, and cocaine-use⁴ variables.

	Total income quartile¹	Number of suppliers²	Unit price²	Cocaine purity²	Cocaine expenses³	Weekly purchases³	Purchase time³	Purchase amount³
Total income quartiel¹
Number of suppliers² (log₁₀)
Unit price² (log₁₀)		−.23
Cocaine subjective purity²
Cocaine expenses³ (log₁₀)	*.71*
Weekly purchases³ (log₁₀)	*.38^a*	*.28^b*	−.28^b		*.47^a*
Purchase time³ (log₁₀)				.24^b		−.32^a
Purchase amount³ (log₁₀)			.48^a		*.32^a*	−*.37^a*	*.28^a*
Daily cocaine use amount⁴ (log₁₀)	*.32^a*	*.30^a*	−*.34^a*	−*.33^a*	*.43^a*	*.28^b*
Cocaine positive urine sample⁴	.21				.23	.33^a	−.29^a	−.21

Correlations in bold italics replicate similar significant relationships in prior studies with regular heroin users (Roddy and Greenwald, 2009; Roddy et al., 2011; Greenwald et al., 2013). Pearson correlation values of |r| ≤ .20 are suppressed for clarity. Correlations of |r| ≤ .23 that were significant at p < .05 without adjustment for multiple comparisons (^ap < 0.01; ^bp < 0.05) were no longer significant using the Benjamini and Hochberg (1995) step-up procedure to control the false discovery rate (19 of 45 correlations declared significant; effective p ≤ .021).