Experiment 2 was a replication and extension of Experiment 2 from Mulatti et al. (2006), examining orthographic neighborhood effects using the same four scripts as in Experiment 1. We again expected the computer-generated print condition to replicate the findings from Mulatti et al. (2006), with a negligible neighborhood effect. We also expected this effect to become more robust when human-generated scripts were used, since top-down lexical activation could better disambiguate features at the letter level.
The observers were 174 Arizona State University students who received course credit. Of these volunteers, 41 were in the computer print, 46 in the computer cursive, 44 in the natural print, and 43 in the natural cursive condition.
The stimuli from Experiment 2 of Mulatti et al. (2006) were generated in the formats used in Experiment 1. Sixty words were used, half from dense orthographic neighborhoods and half from sparse orthographic neighborhoods. The stimuli were balanced on 11 additional variables, as in Experiment 1 (see Mulatti et al., 2006).
Apparatus and procedure
The apparatus and procedure were identical to those of Experiment 1.
Results and discussion
Five participants were excluded from the analyses (one from the computer print, two from the computer cursive, one from the natural print, and one from the natural cursive condition) due to having either average RTs or error rates more than three standard deviations above the respective group mean. One word (“joist”) was excluded from all conditions for eliciting extremely high error rates. Trials with mispronunciations or voice key errors were removed from the RT data prior to the analysis, constituting 3.5% and 1.9% of trials, respectively. The data were trimmed in the same manner as in Experiment 1, resulting in the replacement of 1.3% of the correct RT data. Mean RTs and the derived neighborhood effects per condition are shown in Table 2.
We first examined each script condition individually via linear mixed models, with Subjects and Items as random factors and the fixed factor Orthographic Neighborhood Density (dense, sparse). The computer print condition replicated the findings of Mulatti et al. (2006), producing a nonsignificant 10-ms neighborhood effect. The neighborhood effect was not reliable in the computer cursive condition, but the natural print condition produced a significant 25-ms effect, F(1, 55.27) = 4.54, p = .04, r
pseudo < .01. Finally, the natural cursive condition produced a 19-ms neighborhood effect that was not reliable.
We created an omnibus model, including the factors Script (computer print, computer cursive, natural print, natural cursive) and Orthographic Neighborhood (dense, sparse). A reliable script effect emerged, F (3, 254.11) = 10.55, p < .001, r
pseudo = .11, with slower RTs for naturally produced words. The neighborhood effect was not reliable, but we did observe a Script × Neighborhood interaction, F(3, 9169.20) = 3.19, p = .02, r
pseudo < .01: Generally, the neighborhood effects were larger for words presented in naturally produced scripts (see Table 2).
We next compared the computer-generated and natural scripts in a model with the factors Source (computer, human) and Neighborhood. There was a reliable effect of source, F(1, 270.55) = 18.63, p < .001, r
pseudo = .04, with slower RTs for naturally produced words. A null effect of neighborhood was qualified by a significant Source × Neighborhood interaction, F(1, 8889.78) = 7.18, p = .007, r
pseudo < .01. Critically, the neighborhood effect was larger for words in naturally produced scripts.
Finally, we combined the data from Experiments 1 and 2 in a large model with the factors Experiment (1, 2), Script (computer print, computer cursive, natural print, natural cursive), and Neighborhood (dense, sparse) to assess the relative effect that each script had upon orthographic and phonological neighborhood effects. This analysis produced a marginal experiment effect, F(1, 16921.48) = 3.46, p = .02, r
pseudo < .01, with faster RTs in Experiment 1. We also found a script effect, F(3, 391.79) = 19.71, p < .001, r
pseudo = .13, with higher RTs for naturally produced scripts. A neighborhood effect, F(1, 62.13) = 21.10, p < .001, r
pseudo < .01, reflected faster responding for words from dense neighborhoods. These main effects were qualified by a couple of interactions. First, an Experiment × Script interaction, F(3, 16833.98) = 7.19, p < .001, r
pseudo < .01, was driven by increased RTs for the natural print condition in Experiment 2, relative to Experiment 1. Importantly, a three-way Experiment × Script × Neighborhood interaction also emerged, F(3, 17581.16) = 5.60, p = .001, r
pseudo < .01: Phonological neighborhood effects decreased when moving from artificial to natural stimuli, whereas orthographic neighborhood effects increased.Footnote 1
Again, error rates were generally low across all conditions. The omnibus analysis with the factors Script and Neighborhood produced a marginal main effect of script, F(3, 180.22) = 2.56, p = .057, r
pseudo < .01, with accuracy decreasing for natural stimuli. There was also a Script × Neighborhood interaction, F(3, 9742.23) = 4.11, p = .006, r
pseudo < .01, due to lower accuracy in the natural cursive condition for words from sparse neighborhoods.