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Table 3 Estimated Regression-adjusted Effect of CFS and ISF on Annual Healthcare Expenditures (in US Dollars, $)

From: The economic impact of chronic fatigue syndrome in Georgia: direct and indirect costs

All effects estimated relative to not-fatigued (NF) population, (Standard Errors in Parentheses)
  Linear Ordinary Least Squares (OLS) for Untransformed Cost (y)
  Total Expenditures
($2005)
Inpatient Hospital
Expenditures
($2005)
Ambulatory Provider Visits
($2005)
Rx Medications
($2005)
OTC Medications
($2005)
Other Health Costs
($2005)
Incremental Expenditures attributed to CFS 3084.95*** (799.09) 476.11
(437.06)
1590.70*** (598.98) 919.18*** (293.37) 111.99*** (36.98) -13.03 (12.43)
Incremental Expenditures Attributed to ISF 1119.75** (476.46) 262.89 (254.04) 364.41 (272.99) 448.54*** (142.68) 31.81
(26.80)
12.09
(11.35)
AIC 8303.74 7815.93 7654.30 6969.76 5196.03 6361.90
BIC 8306.15 7818.34 7656.70 6972.17 5198.44 6364.30
  Generalized Linear Model for Untransformed Cost ((y+1)) a
Incremental Expenditures attributed to CFS 3285.54***
(1026.50)
519.95
(582.17)
1343.25**
(587.55)
1241.13*
(694.19)
204.01*
(111.16)
-1.83
(1.28)
Incremental Expenditures Attributed to ISF 1058.27***
(352.68)
71.61
(122.50)
384.73
(250.49)
317.41**
(131.90)
46.83
(30.66)
0.82
(1.37)
AIC 17.33 11.12 16.62 12.54 10.37 2.68
BIC -2045.41 1178.77 -1739.82 -205.99 -925.17 -2767.13
  Two-Part Model (TPM) for Untransformed Cost (y)b
Incremental Expenditures Attributed to CFS 3618.21***
(1285.90)
602.70
(907.17)
1622.69***
(553.52)
1192.25***
(391.32)
189.13***
(54.14)
-16.30
(21.12)
Incremental Expenditures Attributed to ISF 1151.63
(751.45)
128.18
(577.98)
416.12
(322.03)
473.56***
(180.19)
63.30**
(25.14)
30.11
(37.49)
AIC 292.26 150.16 463.65 548.09 564.80 86.65
BIC -2113.67 1359.96 -1250.64 371.70 -328.59 -1313.92
  1. * p < 0.1, ** p < 0.05, ***p < 0.01.
  2. # Full GLM results in Additional file 2, Table S2.
  3. AIC: Akaike's information criterion; BIC: Schwarz's information criterion.
  4. a Generalized Linear Model with Gamma distribution and the log link function for all the categories of healthcare expenditures except for "Other Health Costs" with inverse Gaussian distribution.
  5. b Two-part model: the first part using a logistic regression for binary indicator (healthcare users vs. no-users) and the second part using GLM for positive healthcare costs.