The Music or the Words? Or How Important is the Libretto for an Opera's Aesthetic Success?

2000 ◽  
Vol 18 (2) ◽  
pp. 105-118 ◽  
Author(s):  
Dean Keith Simonton
Keyword(s):  
Multiple Regression ◽  
Predictor Variables ◽  
Literary Genre ◽  
Regression Analyses ◽  
Composite Measure ◽  
Control Variables ◽  
Literary Sources ◽  
The Aesthetic

What are the comparative contributions of composer and librettist to the aesthetic impact of great operas? This question was empirically answered using a sample of 911 operas by fifty-nine composers. The aesthetic success of each opera was gauged by a composite measure that included performance and recording frequencies as well as archival indicators. The predictor variables were both idiographic (e.g., the specific identities of the librettists and the literary sources) and nomothetic (e.g., literary genre, language, librettist's age, and experience). After introducing appropriate control variables, the multiple-regression analyses demonstrated that composers play a much bigger role in determining operatic impact than do librettists or their libretti. The identity of the composers alone accounted for almost half of the variance in aesthetic success. As far as opera is concerned, the music is aesthetically more crucial than are the words.

Effects of Travel and Length of Home Stand/Road Trip on tie Home Advantage

1991 ◽  
Vol 13 (1) ◽  
pp. 42-49 ◽  
Author(s):  
Kerry S. Courneya ◽  
Albert V. Carron
Keyword(s):  
Multiple Regression ◽  
Predictor Variables ◽  
Regression Analyses ◽  
Number Series ◽  
Chi Square ◽  
Future Directions ◽  
Road Trip ◽  
Home Team ◽  
Minor League ◽  
Home Advantage

The present study investigated the effects of season game number, series game number, length of home stand, length of visitor's road trip, home travel, and visitor travel on the home advantage in minor league Double A baseball (N= 1812 games). Initial analysis indicated that the home team won 55.1% of the games (p<.001). Forced-entry multiple regression analyses determined that the combined main and interaction effects of the predictor variables explained less than 1.2% of the variance in win/loss outcome (p>.49). Chi-square analyses revealed that the variable of length of visitor's road trip produced the greatest change in the magnitude of home advantage. When the length of visitor's road trip was cross-tabulated with the length of home stand, me change in home advantage was statistically significant for the home team's later series (p<.05). The implications of these results for the various home advantage explanations are discussed, and future directions for home advantage research are offered.

A Multivariate Study of Hypnotic Susceptibility

1989 ◽  
Vol 9 (1) ◽  
pp. 33-48 ◽  
Author(s):  
Nicholas P. Spanos ◽  
Joyce L. D'Eon ◽  
Anne E. Pawlak ◽  
Christopher D. Mah ◽  
Gary Ritchie
Keyword(s):  
Multiple Regression ◽  
Common Factor ◽  
Predictor Variables ◽  
Regression Analyses ◽  
Hypnotic Susceptibility ◽  
Multivariate Study ◽  
Susceptibility Factors ◽  
Criterion Variables

Twelve variables previously shown to predict hypnotic susceptibility were factor, analyzed. Six of them loaded on a common factor labeled “a positive set toward, imagining.” The items from two hypnotic susceptibility scales were also factor, analyzed, and fell into three factors (one “cognitive” and two motor factors)., Multiple regression analyses using the susceptibility scales and also the three, susceptibility factors as criterion variables indicated that most of the predicted, variance was accounted for by the predictor variables that loaded on the, “imaginative set” factor. Many of the predictor variables did not contribute, significantly to the prediction of the susceptibility measures. Moreover, a number of, predictors, that purportedly assess similar processes, failed to intercorrelate, significantly. Methodological and theoretical implications of these findings are, discussed.

Prediction of Brain Damage in a Neurological Population with Cerebrovascular Accidents

1970 ◽  
Vol 31 (2) ◽  
pp. 595-601 ◽  
Author(s):  
Michael M. Burgess ◽  
Altan Kodanaz ◽  
Dewey K. Ziegler
Keyword(s):  
Multiple Regression ◽  
Brain Damage ◽  
Clinical Population ◽  
Predictor Variables ◽  
Regression Analyses ◽  
Cerebrovascular Accidents ◽  
Sensory Motor ◽  
Intellectual Measures ◽  
Student’S T ◽  
Single Predictor

A total of 15 intellectual and 12 sensory-motor variables were examined as predictors of brain damage in a neurological population with cerebrovascular accidents. Results obtained via Student's t tests and multiple regression analyses demonstrate that it is possible to predict brain damage significantly in this clinical population. Specific conclusions were: (1) as single predictor variables, sensory-motor measures are superior to intellectual measures; (2) brain damage as measured behaviorally is consistent across patient populations in neurological, psychiatric, and neurological sub-groups with CVA; and, (3) multiple variant prediction holds promise for diagnosis of brain damage in a CVA population.

Prediction of Brain Damage in Two Clinical Populations

1970 ◽  
Vol 30 (2) ◽  
pp. 523-532 ◽  
Author(s):  
Michael M. Burgess ◽  
Altan Kodanaz ◽  
Dewey Ziegler ◽  
Howard Greenburg
Keyword(s):  
Multiple Regression ◽  
Brain Damage ◽  
Predictor Variables ◽  
Regression Analyses ◽  
Sensory Motor ◽  
Psychiatric Population ◽  
Student’S T ◽  
Two Populations ◽  
Single Predictor ◽  
Clinical Populations

A total of 15 intellectual and 12 sensory motor variables were examined as predictors of brain damage in a neurological and a psychiatric population. Results obtained via Student's t tests and multiple-regression analyses demonstrate chat it is possible to predict brain damage in both clinical populations. Specific conclusions were: (1) as single predictor variables, sensory motor measures are superior to intellectual measures, (2) brain damage as measured behaviorally is consistent across the two populations, (3) there is a greater incidence of false positives in a psychiatric than a neurological population, and (4) multiple-variant prediction seems to hold promise for identification of brain damage.

Predictors of Self-Esteem with Youth Basketball Players

1996 ◽  
Vol 8 (4) ◽  
pp. 368-378 ◽  
Author(s):  
Vicki Ebbeck ◽  
Moira E. Stuart
Keyword(s):  
Multiple Regression ◽  
Self Esteem ◽  
Perceived Competence ◽  
Predictor Variables ◽  
Regression Analyses ◽  
Conceptual Frameworks ◽  
Basketball Players ◽  
Grade Levels ◽  
The Individual

This investigation examined the extent to which perceptions of competence and importance predicted self-esteem. Players (N = 214) from three grade levels (3–4, 5–6, 7–8) completed questionnaires that assessed perceived basketball competence, as well as each player’s perception of how important it was to himself, his parents, his coach, and his team to be good at basketball. Three nonstepwise multiple regression analyses revealed that the set of predictor variables accounted for 20–28% of the variance in self-esteem across grade levels. The individual predictor variables significantly related to self-esteem were perceived competence and perceived parent importance for Grades 3–4, perceived competence for Grades 5–6, and perceived competence and perceived team importance for Grades 7–8. Perceived competence, however, consistently contributed most substantively to the prediction of self-esteem. These findings are discussed in relation to earlier studies and existing conceptual frameworks.

A Comparison of Selected Measures with Psychological Scale Values of Language Development

1967 ◽  
Vol 10 (4) ◽  
pp. 828-835 ◽  
Author(s):  
Thomas H. Shriner
Keyword(s):  
Language Development ◽  
Multiple Regression ◽  
Complexity Measure ◽  
Predictor Variables ◽  
Age Group ◽  
Regression Analyses ◽  
Systematic Relationship ◽  
Psychological Scale ◽  
The Relationship ◽  
Single Predictor

Four linear multiple—regression analyses were used to determine the best composite for predicting scale values of language development derived from children of four different age categories. For the youngest age group (mean age of four years, seven months), a new measure of language development was evaluated. The results showed that the relationship among the predictor variables change as a function of age. Little systematic relationship was observed between the criterion, scale values of language development, and the predictor variables for children above the age of approximately five years. For children who were younger than five years, the best single predictor was the new measure, a modified length-complexity measure. Until there is further improvement of the length-complexity measure, however, mean length of response is a satisfactory predictor of language for children who are approximately five years of age and younger.

Language and Literacy Predictors of Dialect Density Among School-Age African American Children From Two Geographic Regions

2020 ◽  
Vol 51 (3) ◽  
pp. 807-820
Author(s):  
Lena G. Caesar ◽  
Marie Kerins
Keyword(s):  
African American ◽  
Multiple Regression ◽  
Oral Language ◽  
East Coast ◽  
Geographic Region ◽  
Literacy Skills ◽  
School Age ◽  
Regression Analyses ◽  
Geographic Regions ◽  
American Children

Purpose The purpose of this study was to investigate the relationship between oral language, literacy skills, age, and dialect density (DD) of African American children residing in two different geographical regions of the United States (East Coast and Midwest). Method Data were obtained from 64 African American school-age children between the ages of 7 and 12 years from two geographic regions. Children were assessed using a combination of standardized tests and narrative samples elicited from wordless picture books. Bivariate correlation and multiple regression analyses were used to determine relationships to and relative contributions of oral language, literacy, age, and geographic region to DD. Results Results of correlation analyses demonstrated a negative relationship between DD measures and children's literacy skills. Age-related findings between geographic regions indicated that the younger sample from the Midwest outscored the East Coast sample in reading comprehension and sentence complexity. Multiple regression analyses identified five variables (i.e., geographic region, age, mean length of utterance in morphemes, reading fluency, and phonological awareness) that accounted for 31% of the variance of children's DD—with geographic region emerging as the strongest predictor. Conclusions As in previous studies, the current study found an inverse relationship between DD and several literacy measures. Importantly, geographic region emerged as a strong predictor of DD. This finding highlights the need for a further study that goes beyond the mere description of relationships to comparing geographic regions and specifically focusing on racial composition, poverty, and school success measures through direct data collection.

THE EVALUATION OF SELF-MONITORING ATTRIBUTES

1991 ◽  
Vol 19 (3) ◽  
pp. 205-215 ◽  
Author(s):  
Arts Jiujias ◽  
Peter Horvath
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Regression Analyses ◽  
Self Monitoring

Eighty-six Canadian female undergraduates attributed self-monitoring traits to a target presented on videotape, and evaluated her in terms of liking. Attributed self-monitoring was negatively correlated with attraction to the target and was the only predictor of attraction in a multiple regression analysis. Multiple regression analyses with subscales of attributed self-monitoring as predictors suggested that the evaluations may be the result of the attributed unpredictability of the high self-monitoring prototype.

Phenotypic selection in a population of Crepis tectorum ssp. pumila (Asteraceae)

1992 ◽  
Vol 70 (1) ◽  
pp. 89-95 ◽  
Author(s):  
Stefan Andersson
Keyword(s):  
Life History ◽  
Multiple Regression ◽  
Large Scale ◽  
Demographic Data ◽  
Phenotypic Selection ◽  
Direct Selection ◽  
Surprising Result ◽  
Regression Analyses ◽  
Ecotypic Differentiation ◽  
Crepis Tectorum

A 3-year demographic study was conducted to reveal targets of selection on morphology and life history in a population of Crepis tectorum ssp. pumila, a winter annual plant confined to calcareous grasslands (alvars) on the Baltic island of Öland (south Sweden). I calculated the selection differential to describe the change in the mean value of a character due to selection and used multiple regression analyses to partition the direct effect of selection on the trait from indirect responses of selection on other traits. Rosette leaf number, a convenient measure of plant size, was strongly correlated with both viability and fertility (fitness). There was also a strong relationship between fitness and the extent to which the plants expressed traits characterizing this particular taxon. Multiple regression analyses indicated direct selection favouring plants with deeply lobed leaves and a densely branched stem, two distinctive traits of ssp. pumila believed to be adaptive in the alvar habitat. Only stem height was subject to both direct and indirect selection in the wrong direction; taller individuals were more successful than those with a shorter stem, a surprising result considering the inferred advantage of a short stature in the exposed alvar habitat. Selection on other traits assumed to be ecologically important (germination time, flowering time, and seed size) was found to be either absent or variable in direction when other traits were held constant. The failure of plants to survive to the flowering stage in the last two summers indicates strong selection for plants that produce a high percentage of dormant seeds. Overall, the contemporary selection regime as revealed by demographic data was only partly congruent with predictions regarding historical selection pressures based on large-scale patterns of variation (ecotypic differentiation). Key words: Crepis tectorum, ecotypic differentiation, life history, morphology, phenotypic selection.

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