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. 2019 Aug 14;10:1682. doi: 10.3389/fpsyg.2019.01682

TABLE 7.

Model parameters and summaries of linear and polynomial regression analyses of SLS-Berlin sentence characteristics predicting response times for the subsample of younger adults (<60 years).

Model parameters
Model summary
Estimate SE t-value p-value adj. R2 F-value p-value
Sentence ID
  Linear 65.08 13.5 4.83 <0.001
  Quadratic –1.70 0.40 –4.25 <0.001
  Cubic 0.02 0.00 4.91 <0.001 0.816/0.820* 113.3 <0.001
Number of charactersa
  Linear –265.9 107.7 –2.47 <0.05
  Quadratic 3.09 1.16 2.68 <0.01
  Cubic –0.01 0.00 –2.62 <0.05 0.700/0.687* 59.2 <0.001
Number of syllablesa
  Linear 82.5 7.64 10.8 <0.001 0.606/0.633* 116.5 <0.001
  Quadratic
  Cubic
Number of words
  Linear –167.4 108.5 –1.54 0.12
  Quadratic 13.1 4.75 4.75 <0.01 0.432/0.439* 29.9 <0.001
  Cubic
Number of long words (>6 letters)
  Linear 243.2 37.9 6.42 <0.001 0.346/0.343* 41.2 <0.001
  Quadratic
  Cubic
Number of nouns
  Linear 364.7 64.1 5.69 <0.001 0.292/0.280* 32.4 <0.001
  Quadratic
  Cubic
Flesch
  Linear –2.15 2.08 –1.03 0.31 0.001/−0.002* 1.06 0.31
  Quadratic
  Cubic
Complexity ratingsb
  Linear 994.0 73.1 13.6 <0.001 0.708/0.704* 184.9 <0.001
  Quadratic
  Cubic
Point of decisionb
  Linear –134.3 123.0 –1.09 0.28
  Quadratic 12.5 5.77 2.17 <0.05 0.415/0.401* 28.0 <0.001
  Cubic

All models were checked for influential data points and outliers. aBest model fit after excluding influential cases (i.e., sentence 1) due to a Cook’s distance > 1 and high leverage. bIn a prestudy 19 participants rated the complexity (on a five-point scale ranging from one to five) and marked the point of semantic decision for all 77 sentences. *Adjusted R2 after cross-validation.