Numerous developmental studies assess general cognitive ability, not as the primary variable of interest, but rather as a background variable. Raven's Progressive Matrices is an easy to administer non-verbal test that is widely used to measure general cognitive ability. However, the relatively long administration time (up to 45 min) is still a drawback for developmental studies as it often leaves little time to assess the primary variable of interest. Therefore, we used a machine learning approachregularized regression in combination with cross-validationto develop a short 15-item version. We did so for two age groups, namely 9 to 12 years and 13 to 16 years. The short versions predicted the scores on the standard full 60-item versions to a very high degree r = 0.89 (9-12 years) and r = 0.93 (13-16 years). We, therefore, recommend using the short version to measure general cognitive ability as a background variable in developmental studies. Statement of contribution What is already known on this subject?Raven's Standard Progressive Matrices is widely used to measure cognitive ability as background variable in developmental studies.A drawback is its long administration time (up to 45 min), and it would therefore be helpful to develop a shortened version.Although short versions of the RSPM exist, no short version is suitable for children and adolescents. What does this study add?We used a machine learning approach to develop shortened 15-item versions for two age groups (9-12 and 13-16 years).This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Making better decisions typically requires obtaining information relevant to that decision. Adolescence is marked by increasing agency in decision-making and an accompanying increase in impulsive decisions, suggesting that one characteristic of adolescent decision-making is a tendency to make less-informed decisions. Adolescents could also be especially averse to the effort associated with acquiring relevant information to make decisions. To investigate this possibility, we recruited adolescents (M age = 15.02 years) in upper-secondary schools and young adults (M age = 20.53 years) attending university in the Netherlands to complete an effort-based information sampling task, in which participants could sample information until obtaining sufficient evidence to make a decision. Effort costs for sampling were systematically varied. Surprisingly, adolescents sampled more evidence than adults before making decisions when sampling effort costs were low. Further, adolescents obtained stronger evidence prior to their decisions than adults as effort costs increased, exhibiting less aversion to effort costs associated with information sampling. Exploratory computational models supported these findings. Both adolescents and adults used simple heuristics in deciding whether to sample additional information or make a final decision, and adolescents sought a higher evidence threshold before deciding compared with adults. These results suggest that adolescents may require more certainty to make decisions compared with adults and be less averse to effort costs when gathering information to aid decisions.
Introduction Analysis of covariance (ANCOVA) remains a widely misunderstood approach for dealing with group differences on potential covariates (Miller & Chapman, 2001). This misunderstanding of the ANCOVA has a long history and its discussion is dispersed across fields and journals, making it difficult to obtain a systematic overview. Here we present a network method to organize the results of a literature search conducted by 44 Master's students as part of the 2016 University of Amsterdam course "Good Research Practices". The ANCOVA Pitfall Dora wants to assess whether, in her own university, men earn more than women. She has access to the salaries of a subset of researchers, and, as expected, men earn significantly more than women (p < .005). But wait! The men in her sample are also older than the women, and this confounds the results: perhaps the salary difference is due to age rather than gender. To address this confound and "control for" age, Dora includes age as a covariate in an ANCOVA. This procedure is tempting but statistically problematic. The ANCOVA is easier to interpret correctly when age influences salary but does not differ across the groups. As explained in Miller and Chapman (2001; but see chapter 10 in Judd, McClelland, & Ryan, 2011, and Field, 2013, pp. 484-486), when groups differ on a covariate (e.g., age), removing the variance associated with the covariate also removes the shared variance associated with the group (e.g., gender). As a result, the grouping variable loses some of its representativeness. This occurs mostly when groups are pre-existing and are not obtained by random assignment (Jamieson, 2004). As an example, assume one has access to the height of several mountain peaks in the Himalayas and the Pyrenees (Cohen & Cohen, 1983). One may test whether the mountain ranges differ in height and it may be tempting to include air pressure as a covariate; after all, air pressure differs across the
Adolescence is marked by increased agency in decision-making and an accompanying increase in risky and impulsive decision-making. Making better decisions typically requires obtaining information relevant to that decision, suggesting that one explanation for increased risky and impulsive behavior in adolescence is a tendency to make ill- informed decisions. Adolescents could be especially averse to the effort associated with acquiring information. To investigate this possibility, we recruited adolescents (13-17 years old) in upper-secondary schools and young adults (17-47 years old) attending university in the Netherlands to complete an effort-based information sampling task, in which participants could sample information until obtaining sufficient evidence to make a decision, and effort costs for sampling were systematically varied. Surprisingly, adolescents sampled more evidence than adults before making decisions when sampling effort costs were low; further, adolescents obtained stronger evidence prior to their decisions than adults as effort costs increased, exhibiting less aversion to effort costs associated with information sampling. Computational models supported these findings. Both adolescents and adults used simple heuristics in deciding whether to sample additional information or make a final decision, and adolescents sought a higher evidence threshold before deciding compared with adults. These results suggest that adolescents may require more certainty to make decisions compared with adults and be less averse to effort costs when gathering information to aid decisions.
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