Multiple regression in behavioral research /

Multiple regression in behavioral research /

Show other versions (1)

Saved in:

Bibliographic Details
Main Author:	Kerlinger, Fred N.
Format:	Texto biblioteca
Language:	d
Published:	New York : Holt, Rinehart and Winston, 1973
Subjects:	MULTIPLE REGRESSION, Pedhazur Elazar J.,
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multiple regression in behavioral research
by: Kerlinger, Fred N., et al.

Semiparametric regression /
by: Ruppert, David 23479
Published: (2003)

Biplots in Reduced-Rank Regression
by: ter Braak, C.J.F., et al.

Nonlinear regression /
by: Seber, G. A. F. 10036
Published: (2003)

Methodology adjusting for least squares regression slope in the application of multiplicative scatter correction to near-infrared spectra of forage feed simples
by: Dhanoa, M.S., et al.
Published: (2023)

Predicting the metabolizable energy content of corn for ducks: A comparison of support vector regression with other methods
by: Faridi, A., et al.
Published: (2013)

Statistical analysis of nitrogen use efficiency in Northeast China using multiple linear regression and Random Forest
by: Liu, Ying Xia, et al.

Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
by: Montenegro Díaz, Alvaro Mauricio
Published: (2020-02-26T15:12:29Z)

Statistical approaches in weed research: choosing wisely.
by: CONCENCO, G., et al.
Published: (2018-09-10)

Prediction of the percentages of cows', goats' and ewes' milk in “Ibérico” cheese by electrophoretic analysis of whey proteins
by: Molina, Elena, et al.
Published: (1995-07)

Phosphorus transport in different soil types and the contribution of control factors to phosphorus retardation
by: Ma, Jie, et al.

Multiple regression in behavioral research; explanation and prediction /Elazar J. Pedhazur
by: Pedhazur, Elazar J.
Published: (1982)

Food security and poverty reduction effects of agricultural technologies adoption − a multinomial endogenous switching regression application in rural Zimbabwe
by: Amankwah, Akuffo, et al.
Published: (2024-05)

Stream Temperature Modeling and Monitoring: Multiple Regression Stream Temperature Model
by: US Forest Service Rocky Mountain Research Station Boise Aquatic Sciences Lab (17480496)
Published: (2019)

Foundations of behavioral research
by: Kerlinger, Fred N.

Modelo de superfície de resposta com algumas variáveis auxiliares adicionais.
by: MORAIS, A. R. de, et al.
Published: (1996-03-21)

Water stress in modern upland rice cultivars: a multivariate study between physiological traits and yield.
by: QUILOANGO-CHIMARRO, C. A., et al.
Published: (2024-01-17)

Applied multiple regression : correlation analysis for the behavioral sciences /
by: Cohen, Jacob
Published: (1983)

Pedotransfer functions to estimate bulk density from soil properties and environmental covariates : Rio Doce basin
by: de Souza, E., et al.

Chemometric appraisal of lignin pyrolytic assemblages from Eucalyptus woods relevant for pulping in Uruguay
by: Galetta, M. A., et al.
Published: (2014-08)

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models
by: Buchaillot, María Luisa, et al.
Published: (2022-03-24)

Using precision agriculture and remote sensing techniques to improve genotype selection in a breeding program
by: Rodrigues Junior, F. A., et al.
Published: (2014-07)

Comparative analysis shows that bacterivory, not viral lysis, controls the abundance of heterotrophic prokaryotic plankton
by: Pedrós-Alió, Carlos, et al.
Published: (2000-04)

Quantifying crown morphology of mixed pine-oak forests using terrestrial laser scanning
by: Uzquiano, Sara, et al.
Published: (2021-12-06)

Perceptions on Smart Gas Meters in Smart Cities for Reducing the Carbon Footprint
by: Hurst, W.S.K., et al.

Source identification of heavy metals in surface paddy soils using accumulated elemental ratios coupled with mlr
by: Ma, Jie, et al.

Pedodiversity deserves attention in plant biodiversity research
by: Ibáñez, J. J., et al.
Published: (2014-11-20)

Factores ambientales que influyen en el número de curva en una cuenca, con diversos usos de suelo, del centro de México.
by: Espejel Rodríguez, Aketzalli
Published: (2020-04)

Evaluation of statistical and geostatistical models of difgital soil properties mapping in tropical mountain regions.
by: CARVALHO JUNIOR, W. de, et al.
Published: (2014-08-13)

Simulation of damage in winter wheat caused by the grain aphid Sitobion avenae. 3. Calculation of damage at various attainable yield levels.
by: Rossing, W.A.H.

SAS system for linear models / [et al.]
by: Littell, Ramon C.
Published: (1991)

A Methodology for Updating International Middle-Class Lines for the Latin American and Caribbean Region
by: Fernandez, Jaime, et al.
Published: (2023-05-22)

Equations of bark thickness and volume profiles at different heights with easy-measurement variables
by: Cellini, Juan Manuel, et al.
Published: (2012)

Multiple regression in practice /
by: Berry, William Dale
Published: (1985)

Estimating topsoil water content of clay soils with data from time-lapse electrical conductivity surveys
by: Martínez, Gonzalo, et al.
Published: (2012-06)

Simplivariate Models: Uncovering the Underlying Biology in Functional Genomics Data
by: Saccenti, E., et al.

Quantifying preferences of farmers and veterinarians for national animal health programs : The example of bovine mastitis and antimicrobial usage in Switzerland
by: van den Borne, Bart H.P., et al.

Interaction effects in multiple regression /
by: Jaccard, James
Published: (1990)

Yield prediction of four bean (Phaseolus vulgaris) cultivars using vegetation indices based on multispectral images from UAV in an arid zone of Peru
by: Saravia Navarro, David, et al.

Modelo matemático para estimativa da temperatura média diária do ar no Estado de Goiás.
by: ANTONINI, J. C. dos A., et al.
Published: (2009-07-14)

Resource Map