Your English writing platform
Free sign upSuggestions(5)
Exact(10)
Multiple regression indicated predictors of satisfaction were levels of education and diagnosis.
Analyses by multiple regression indicated that pressure has a major linear effect on oil yield, whilst temperature and time have a lesser impact.
Analysis by multiple regression indicated that pressure and time have a major linear effect on the extraction yield and extract composition.
Furthermore, hierarchical multiple regression indicated that the four psychopathy factors, gender, age, study hours, and course explain 14% of variance in grade outcome.
Stepwise multiple regression indicated that the strongest independent predictors of QOL were the child's anxiety level, age, sex, and a measure of the child's tendency to minimize or exaggerate symptoms.
Results of stepwise multiple regression indicated that the best subsets for predicting adolescent menstrual distress, including age, mother's occupation, menstrual pain, and menstrual attitude, accounted for 59% of total variance.
Similar(50)
Of these two variables the multiple regression indicates that the number of GPs was probably the more important predictor of total TCI score.
For all outcome variables except measles immunization, multiple regression indicates that children living in an urban area were less likely to be immunized than those living in rural areas (BCG OR 0.54, 95% CI 0.44 0.66, P < 0.001; DTP3 OR 0.74, 95% CI 0.64 0.87, P < 0.001; full immunization OR 0.73, 95% CI 0.64 0.84, P < 0.001).
Multiple regressions indicated that positive influences on school bonding following program participation partially mediated effects on alcohol use.
Calculations from multiple regressions indicated that compression cone firmness and dynamic stiffness have stronger influences on static stiffness than breakage force strength.
Calculations from multiple regressions indicated that compression cone hardness and dynamic stiffness have stronger influences on breaking force strength than static stiffness (deformation).
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com