Studies which provide norms of Likert ratings typically report per-item summary statistics. Traditionally, these summary statistics comprise the mean and the standard deviation (SD) of the ratings, and the number of observations. Such summary statistics can preserve the rank order of items, but provide distorted estimates of the relative distances between items because of the ordinal nature of Likert ratings. Inter-item relations in such ordinal scales can be more appropriately modelled by cumulative-link mixed effects models (CLMMs). In a series of simulations, and with a reanalysis of an existing rating norms dataset, we show that CLMMs can be used to more accurately norm items, and can provide summary statistics analogous to the traditionally reported means and SDs, but which are disentangled from participants’ response biases. CLMMs can be applied to solve important statistical issues that exist for more traditional analyses of rating norms.

LexOPS is an R package and user interface designed to facilitate the generation of word stimuli for use in research. Notably, the tool permits the generation of suitably controlled word lists for any user-specified factorial design and can be adapted for use with any language. It features an intuitive graphical user interface, including the visualization of both the distributions within and relationships among variables of interest. An inbuilt database of English words is also provided, including a range of lexical variables commonly used in psycholinguistic research. This article introduces LexOPS, outlining the features of the package and detailing the sources of the inbuilt dataset. We also report a validation analysis, showing that, in comparison to stimuli of existing studies, stimuli optimized with LexOPS generally demonstrate greater constraint and consistency in variable manipulation and control. Current instructions for installing and using LexOPS are available at https://JackEdTaylor.github.io/LexOPSdocs/.

No abstract

Studies which provide norms of Likert ratings typically report per-item summary statistics. Traditionally, these summary statistics comprise the mean and the standard deviation (SD) of the ratings, and the number of observations. Such summary statistics can preserve the rank order of items, but provide distorted estimates of the relative distances between items because of the ordinal nature of Likert ratings. Inter-item relations in such ordinal scales can be more appropriately modelled by cumulative link mixed effects models (CLMMs). In a series of simulations, and with a reanalysis of an existing rating norms dataset, we show that CLMMs can be used to more accurately norm items, and can provide summary statistics analogous to the traditionally reported means and SDs, but which are disentangled from participants’ response biases. CLMMs can be applied to solve important statistical issues that exist for more traditional analyses of rating norms.

For the quantitative analysis of a 65 Cu-30 Ni-S Fe alloy, a 96 Cu-3 Si-1 Mn alloy, and a 78 Cu-20 Zn-2 Al alloy, the Ziebold empirical method of correcting electron-microbeam-probe data was used. Four binary standards, of single-phase Cu-Ni, Ni-Fe, Cu-Mn, and Cu-Zn alloys, were cast and the a correction factor found for each element in each binary by Ziebold's relationship (1 – K)/K – α (1 – C)/C, where K – I/I0 found in the probe and C is the weight fraction found by wet chemistry. The ARL EMX probe was used at 30 kV with a 25-μ beam diameter to negate inhomogeneities. Experience with these binaries indicated that in the presence of secondary fluorescence, the experimental α values agreed poorly with theoretically calculated K values; however, where secondary fluorescence was negligible, agreement between the experimental and theoretical α values was good. The α values for Cu–Si, Cu–Al, Al-Zn, and Mn–Si alioys, were therefore calculated from the theoretical equations. The α values for Cu–Fe alloys were also calculated from theoretical considerations because single-phase binaries over the composition range of interest could not be made for this system. All these α values were used in Ziebold's ternary equations to correct probe data (again using a 25-μ beam) from specimens of Cu–Ni-Fe, Cu–Si–Mn, and Cu-Zn–Al. These results were compared to wet-chemistry analyses for the same specimens with quite good correlation between the two sets of data. Calibration curves for the binary systems Cu-Ni, Cu-Fe, Ni-Fe, Cu-Mn, Cu-Si, Mn-Si, Cu-Al, Cu-Zn, and Al-Zn were made and are reproduced.