Skip to main content

Table 2 Associations between antibody responses and complement fixation activity over time using linear mixed modeling (n = 30)

From: Induction and decay of functional complement-fixing antibodies by the RTS,S malaria vaccine in children, and a negative impact of malaria exposure

Factora bb (s.e.) 95% CI p valuec f 2d
IgG1     0.38
 Linear term 1.10 (0.16) 0.78, 1.41 < 0.001  
 Interaction term − 0.28 (0.05) − 0.38, − 0.18 < 0.001  
IgG2     0.02
 Linear term 0.11 (0.13) − 0.14, 0.37 0.388  
 Interaction term − 0.01 (0.05) − 0.10, 0.08 0.805  
IgG3     0.18
 Linear term 0.54 (0.15) 0.24, 0.83 < 0.001  
 Interaction term − 0.07 (0.05) − 0.18, 0.03 0.177  
IgG4     0.02
 Linear term 0.21 (0.86) − 1.47, 1.90 0.802  
 Interaction term 0.07 (0.31) − 0.53, 0.68 0.808  
IgM     0.03
 Linear term − 0.21 (0.18) − 0.57, 0.38 0.233  
 Interaction term − 0.02 (0.07) − 0.11, 0.15 0.792  
  1. aLinear mixed modeling (LMM) analyses where the natural log of C1q-fixation was regressed on the natural log of antibody responses (linear term) conditioning on other antibody response factors to provide an independent association. This LMM model included a term for the natural log of time (not shown) and relaxed the constraint of a consistent association between C1q-fixation and antibody responses across time (interaction term). The LMMs applied a random intercept for study participant and random slope for time
  2. bRegression coefficient (b) and standard error (s.e.) represent the percent change in participant C1q-fixation level for a percent increase in antibody responses
  3. cProbability values based on Wald statistics
  4. dCohen’s f2 represents the ratio of the unique variance explained by a specific antibody response factor to the variance explained by an intercept-only model. Higher values indicate a stronger effect