Bootstrap Standard Error and Confidence Intervals for the Difference Between Two Squared Multiple Correlation Coefficients

2008 ◽  
Vol 69 (4) ◽  
pp. 566-584 ◽  
Author(s):  
Wai Chan
Keyword(s):  
Confidence Intervals ◽  
Standard Error ◽  
Correlation Coefficients ◽  
Multiple Correlation ◽  
The Difference ◽  
Multiple Correlation Coefficients

scholarly journals Spectral Noise Levels and Roughness Severity Ratings for Normal and Simulated Rough Vowels Produced by Adult Males

1970 ◽  
Vol 13 (3) ◽  
pp. 489-502 ◽  
Author(s):  
Frank E. Sansone ◽  
Floyd W. Emanuel
Keyword(s):  
Correlation Coefficients ◽  
Adult Males ◽  
Noise Levels ◽  
Multiple Correlation ◽  
Acoustic Spectrum ◽  
Spectral Components ◽  
Multiple Correlation Coefficients ◽  
The Individual ◽  
Spectral Ranges ◽  
The Relationship

Twenty normal-speaking adult males sustained productions of each of the vowels /u/, /i/, /Λ/, /a/, and /æ/ first normally and then with simulated vocal roughness at one intensity. A tape recording of each production was rated for roughness on a five-point equal-appearing-intervals scale by 11 trained judges and was also analyzed to produce its 3-Hz bandwidth frequency-by-amplitude acoustic spectrum. The median roughness rating and the level of inharmonic spectral components, i.e., noise components, for each production were examined and related. Noise levels for the productions of each vowel averaged over selected spectral ranges between 100 Hz and 8000 Hz correlated highly with the median roughness ratings for those productions. Multiple correlation coefficients indicating the relationship between the median roughness rating and multiple measures of spectral noise in the range from 100 Hz to 2600 Hz for the individual productions of each test vowel were high (≥0.97) and significant for all five vowels.

Measuring Exercise Self-Efficacy in Pregnant Women: Psychometric Properties of the Pregnancy-Exercise Self-Efficacy Scale (P-ESES)

2013 ◽  
Vol 21 (3) ◽  
pp. 349-359 ◽  
Author(s):  
Helen W. Bland ◽  
Bridget F. Melton ◽  
Elaine S. Marshall ◽  
Jacquelyn A. Nagle
Keyword(s):  
Pregnant Women ◽  
Psychometric Properties ◽  
Self Efficacy ◽  
Correlation Coefficients ◽  
Validity And Reliability ◽  
Multiple Correlation ◽  
Components Analysis ◽  
Multiple Correlation Coefficients ◽  
Original Measure ◽  
Activity Questionnaires

Background and Purpose: This study assessed the psychometric properties of a modified self-efficacy scale—the Pregnancy-Exercise Self-Efficacy Scale (P-ESES). Methods: Pregnant women completed the P-ESES and physical activity questionnaires (N = 88). Results: Internal consistency was confirmed by Cronbach’s alpha (α = 0.838) and equal-length Spearman–Brown (α = 8.22). Squared multiple correlation coefficients were calculated showing 9 of 10 items with values greater than the desired .5. A nonrotated exploratory principal components analysis confirmed the same 9 of 10 items loaded on a single factor, accounting for 46.1% of the variance. Each item had an acceptable load value of .40 or higher. Conclusions: Initial testing of the P-ESES confirmed validity and reliability with the exception of 1 item from the original measure: “Exercising without physician approval.”

Interrelationships among Food Intake, Somatic Traits, and Physical Fitness in 10.5- to 15.5-Year-Old Children From Eastern Poland

1998 ◽  
Vol 8 (4) ◽  
pp. 388-400 ◽  
Author(s):  
Grzegorz Raczyński ◽  
Jan Czeczelewski ◽  
Maciej Skład ◽  
Romuald Stupnicki
Keyword(s):  
Food Intake ◽  
Physical Fitness ◽  
Energy Intake ◽  
Correlation Coefficients ◽  
Dietary Quality ◽  
Multiple Correlation ◽  
Dietary Recall ◽  
Somatic Development ◽  
Nutrition Quality ◽  
Multiple Correlation Coefficients

The aim of the study was to establish the relationships between energy intake and dietary quality with somatic variables and physical fitness. Energy intake and nutrition quality were assessed from 24-hr dietary recall questionnaires, and physical fitness was measured by applying the EUROFIT tests. Interrelationships between all those variables (simple, partial, and multiple correlation coefficients) were computed from standardized values. The somatic and physical fitness variables related more strongly on the nutrition quality than on the energy intake. Well-nourished children were taller, heavier, and more physically fit than the poorly nourished ones. We believe that dietary quality affected physical fitness indirectly by influencing somatic development. Energy intake did not contribute significantly to the total variance of the physical fitness factor.

Managerial Implications of Extended Breaks on Predicting Performance Times for Industrial Tasks

1992 ◽  
Vol 36 (11) ◽  
pp. 825-828
Author(s):  
Robert Yearout ◽  
Darlene Hewitt ◽  
Donald Lisnerski ◽  
Kelli Sprague
Keyword(s):  
Cognitive Task ◽  
Correlation Coefficients ◽  
Exponential Model ◽  
Multiple Correlation ◽  
Performance Time ◽  
Predicting Performance ◽  
Managerial Implications ◽  
Multiple Correlation Coefficients ◽  
Performance Times ◽  
Break Period

Production Managers and Industrial Engineers have relied upon learning (progress) curves for over fifty years. However, until recently only the impacts of extended breaks on performance time predictions were considered. This study examined the effect of breaks on two typical simulated industrial tasks. Fifty-eight subjects performed either the traditional peg-board, a low cognitive task, or a spreadsheet graphic, a moderately-high cognitive task, for 28 iterations. Upon completion of the assigned task, a break period that ranged from 2 to 83 days was randomly assigned to each subject. After the break, subjects replicated their assigned task. Regression analysis was used to select the best model to predict the performance time for the first iteration after a break. An exponential model was selected for the low cognitive task and a multiple linear model for the moderately-high cognitive task. Both models selected were no-intercept models and had multiple correlation coefficients of 0.729 and 0.897 respectively. The ability to accurately predict the first iteration time after a break is a key element in calculating time lost to forgetting and determining the forgetting function. These models may be useful in assisting production managers and industrial engineers in establishing more realistic progress curves and accurate standard times, thus reducing excessive idle time.

Immunization Coverage and Infant Mortality Rate in Developing Countries

1994 ◽  
Vol 7 (4) ◽  
pp. 228-232 ◽  
Author(s):  
Akira Shimouchi ◽  
Kotaro Ozasa ◽  
Kyohei Hayashi
Keyword(s):  
Health Care ◽  
Developing Countries ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Correlation Coefficients ◽  
Immunization Coverage ◽  
Infant Mortality Rate ◽  
Multiple Correlation ◽  
Primary Health ◽  
Multiple Correlation Coefficients

We examined whether immunization coverage (IMC) is one of the predictors of infant mortality rate (IMR), as a single indicator representing the availability of primary health care (PHC) services in developing countries. Multiple regression analysis showed that partial correlation coefficients for IMR with immunization coverage (-0.224), logarithm of per capita GNP (-0.294), total fertility rate (0.269), and adult literacy rate (-0.325) were all statistically significant (p < 0.001) in 97 developing countries which make up more than 97% of the population in all developing countries of the world. Multiple correlation coefficients of IMR with these four variables in 97 countries was 0.921. Thus, more than 80% of variation of IMR in developing countries were explained by the variation of the four variables. The study also showed that IMC was well correlated (simple correlation) with the four indicators of the availability of primary health care services: access to local care (0.730), care of pregnant women (0.603), delivery care (0.666), and infant care (0.553), all of which were statistically significant (p < 0.001) in the 48 developing countries which make up 42% of the population of all developing countries. Multiple correlation coefficients of these four variables was 0.787. About 60% of the variation of IMC will be explained by the variation of the four variables. Thus we conclude that immunization coverage is one of the main predictors of the infant mortality rate. It represents one of the health intervention components which can be used as a proxy indicator of the availability of PHC service in developing countries. Asia Pac J Public Health1994;7(4): 228-32.

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