Rauh et al. model fitting, for the purpose of determin- ing the robustness of our results with respect to alternate methods. Covariates were ini- tially selected based on prior literature and retained in the models if associated with either CPF exposure or the WISC-IV scales (p < 0.10 in univariate analyses). Multiple linear regression was used to test the effects of prenatal CPF exposure on each 7-year WISC-IV Index. We examined residuals for normality and homoscedasticity and detected no problems. In addition, we employed the least absolute shrinkage and selection opera- tor (LASSO), a shrinkage with selection pro- cedure that provides a more parsimonious approach to covariate selection and model fitting (Houwelingen 2001; Tibshirani 1996). This method minimizes the usual sum of squared errors, with a bound on the sum of the absolute values of the coefficients, thereby shrinking very unstable estimates toward zero, excluding redundant/irrelevant covariates, and avoiding overfitting (Zhao and Yu 2006). We used Sobel’s indirect test to assess the influ- ence of child behaviors on the estimates of CPF effect (MacKinnon et al. 2002; Sobel 1982). We used Sobel’s indirect test to assess mediation (MacKinnon et al. 2002; Sobel 1982). Interaction terms including CPF and each additional covariate were tested in the models. Effect estimates, 95% confidence intervals (CIs), and p-values were calculated for all analytic procedures. Results were con- sidered significant at p < 0.05. Results The retention rate for the full cohort was 82% at the 7-year follow-up, with no significant sociodemographic differences between sub- jects retained in the study and those lost to follow-up (data not shown). Table 1 lists char- acteristics of the study sample with complete data on all variables (n = 265). Study families were predominantly low income, with 31% of mothers failing to complete high school by child’s age 7 years, and 66% never married. The sample was largely full term (only 4% of children in the sample were < 37 weeks gestational age at delivery) and included very few low-birth-weight infants because a) we excluded high-risk pregnancies from the study cohort, and b) the timing of air monitoring in the third trimester of pregnancy eliminated early deliveries. CPF exposure levels ranged from non- detectable to 63 pg/g. We imputed exposure levels in participants with nondetectable CPF (n = 115, 43%) according to assay-specific LOD values, with 93 subjects having LOD equal to 0.5 pg/g and 22 subjects having LOD equal to 1 pg/g. Correlation analyses for exposures and cognitive outcomes. Unadjusted correla- tions between prenatal CPF exposure and Table 1. Demographic characteristics of the sample at 7-year follow-up (n = 265). Characteristic Home qualitya Income < $20,000 ≥ $20,000 Maternal educationb Years < High school degree High school degree Maternal IQc Maternal race/ethnicityd Dominican African American Marital status Never married Ever married Child sex Male Female Gestational age (weeks) Birth weight (g) Child age at testing (months) Prenatal chemical exposures ETSe Exposed Not exposed Cotinine (ng/mL)f Lead (μg/dL)f CPF (pg/g)f PAHs (ng/m3)g n (%) or mean ± SD (range) 40.23 ± 4.81 (23–52) 12.22 ± 2.58 (1–20) 85.97 ± 13.46 (60–135) 138 (52) 127 (48) 82 (31) 183 (69) 146 (55) 119 (45) 175 (66) 90 (34) 117 (44) 148 (56) 39.3 ± 1.5 (30–43) 3389.8 ± 493.5 (1,295–5,110) 85.97 ± 2.65 (74.90–101.5) 93 (35) 172 (65) 0.25 ± 0.92 (0.01–8.78) 1.09 ±.88 (0.15–7.45) 3.17 ± 4.61 (0.09–32) 3.37 ± 3.51 (0.50–36.5) log-transformed WISC-IV Composite Indices (Verbal Comprehension, Working Memory, Processing Speed, and Perceptual Reasoning), and Full-Scale IQ showed significant inverse associations between CPF exposure and a) Working Memory (r = –0.21, p = < 0.0001) and b) Full-Scale IQ (r = –0.13, p = 0.02). We observed a weak inverse correlation between CPF and Perceptual Reasoning (r = –0.09, p = 0.09), while associations of CPF with Verbal Comprehension (r = –0.04) and Processing Speed (r = –0.01) had p-values > 0.05. Umbilical cord lead was not signifi- cantly correlated with CPF level (r = –0.08, p = 0.49) or WISC-IV scores (all p-values > 0.05) among the 89 children with lead data available. Lead was not significantly correlated with CPF level (r = –0.08, p = 0.49, as previ- ously reported by Rauh et al. 2006) or with 7-year WISC-IV scores (all p-values > 0.05) among the 89 children with available data. To avoid excluding observations without lead data, we did not include lead as a covariate in regression models. ETS and (to a lesser extent) PAH were correlated with CPF (Spearman coefficients: 0.113, p = 0.01, and 0.07, p = 0.09, respectively) but were not signifi- cantly correlated (using the Mann–Whitney test for the dichotomous ETS variable) with any WISC-IV index (coefficients ranged from –0.02 to 0.03, and p-values ranged from 0.39 to 0.87). Birth weight was not significantly associated with any of the WISC-IV indices (all p-values > 0.05) and was not included in the final models. Spline regression analysis. Examination of the smoothed cubic spline regression curves, superimposed over scatterplots, indicates subtle differences in shape of the functions (Figure 1). The log-transformed Working Memory Index and Full-Scale IQ appear to be approximately linear, whereas the other functions show some curvature across exposure levels, with sparse observations at the highest exposures. Using the Davidson–MacKinnon test for compari- son of non-nested models (Davidson and MacKinnon 1981), we compared models in which CPF was entered as a single continu- ous outcome with those in which CPF was modeled using B-splines. We failed to reject the hypothesis that the model with CPF as a continuous measure is adequate against the alternative that the model with CPF modeled using splines provided a better fit for each WISC-IV Index (p-values: Verbal Comprehension Index = 0.07, Perceptual Reasoning Index = 0.08, Processing Speed Index = 0.59, Working Memory Index = 0.40, and Full-Scale IQ = 0.08). Estimation of linear models. Table 2 lists the estimated B-coefficients, 95% CIs, and p-values for the exposure variable and cova- riates for the best-fitting linear regression models predicting each WISC-IV outcome. aAs measured by the HOME inventory. bCompleted years of education at child’s age 7 years. cAs measured by TONI-3. dSelf-reported race/ethnicity (African American = 1; Dominican = 0). eSelf-reported ever exposed to secondhand smoke in pregnancy (yes = 1; no = 2). fMeasured in cord blood. gMeasured by personal air sampling. 1198 ovlume 119 | number 8 | August 2011 • Environmental Health Perspectives