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Table 2 Serum results of mixed models

From: Serum and cerebrospinal fluid immune mediators in children with autistic disorder: a longitudinal study

  Limit of detection (pg/mL) % outside limit of detection Within df Test statistics from mixed model
Group (1 df) Age (2 df) Age2 (2 df)
    F(p) F(p) F(p)
Cytokines
 IL-1α 0.35 15 149 0.01 (.94)   
 IL-1RAa 0.09 49 193 0.27 (.85)   
 IL-1βa 0.03 49 193 0.23 (.85)   
 IL-2 0.03 29 117 0.46 (.81)   
 sIL-2RAa 0.30 33 189 0.43 (.81) 7.72 (.01) 3.65 (.13)
 IL-3a 0.01 46 193 4.80 (.13)   
 IL-4 0.04 28 116 0.59 (.77)   
 IL-5 0.01 10 163 0.2 (.86)   
 IL-6a 0.06 34 193 0.23 (.85)   
 IL-7 0.03 12 156 0.89 (.70)   
 IL-9 0.01 6 171 0.03 (.93)   
 IL-10 0.01 27 119 0.1 (.88) 3.97 (.11) 4.5 (.07)
 IL-12p40 0.57 16 146 1.12 (.60) 5.81 (.04)  
 IL-12p70 0.05 15 147 1.27 (.60)   
 IL-13a 0.01 37 193 0.62 (.77)   
 IL-15a 0.17 52 193 0.40 (.81)   
 IL-17 0.01 5 177 0.10 (.88)   
 IFNα2 0.12 5 174 0.79 (.73)   
 IFNγ 0.04 2 186 0.02 (.93)   
 TNFα na 0 190 0.02 (.93) 13.10 (<.001)  
 TNFβ 0.02 27 123 0.04 (.93)   
 TGFα 0.02 12 153 1.12 (.60)   
Growth factors
 EGF 2.70 7 170 8.64 (.04)   
 G-CSF 1.65 1 186 0.10 (.88) 3.99 (.11)  
 GM-CSF 1.85 2 186 0.36 (.81)   
 VEGF 3.36 3 185 2.26 (.43)   
 FGF-2 4.08 8 166 0.02 (.93)   
 FLT-3La 0.04 57 193 1.19 (.60)   
 sCD40La 1 671 700 53 193 15.0 (<.001)   
Chemokines
 CCL2 (MCP-1) na 0 192 2.04 (.44)   
 CCL3 (MIP-1α) 0.03 8 169 1.59 (.53)   
 CCL4 (MIP-1β) 2.9 1 191 0.15 (.88)   
 CCL7 (MCP-3) 0.73 21 132 0.59 (.77)   
 CCL11 (EOTAXIN) 17.06 1 188 0.01 (.94)   
 CCL22 (MDC) na 0 190 4.73 (.13) 7.92 (.01)  
 CXCL1 (GRO) na 0 193 1.65 (.53)   
 CXCL8 (IL-8) na 0 189 0.12 (.88) 1.63 (.53) 5.18 (.07)
 CXCL10 (IP-10) na 0 192 2.59 (.42)   
 CX3CL1 (FRACTALKINE) 2.1 26 119 0.02 (.93)   
  1. Note: df = degrees of freedom; na = not applicable. Out-of-range values were below the limit of detection for all variables except sCD40L, for which out-of-range refers to values above the limit of detection. Out-of-range values were set to missing, except where the % outside the limit of detection was ≥30%. Those variables were analyzed as categorical (out-of-range versus detectable), modeled with a binary distribution and logit link. A series of nested models were tested; sequential models for quadratic, linear, and no effect of age were tested. Where a linear or quadratic term was significant, a contrast statement was used to determine the difference in linear slope or quadratic shape between groups; in no case was this contrast statistically significant. Raw p values were used to determine the best-fitting model; FDR-adjustment was performed after this model was selected and are presented in the table; many terms did not remain significant after correction. All models included sex as a covariate and a random effect of intercept to control for observations correlated within subject
  2. aVariables that were analyzed as categorical (out-of-range versus detectable) and modeled with a binary distribution and logit link. The remaining variables were analyzed as Ln-transformed continuous variables with a Gaussian distribution