Multivariate Analysis in the Human Services

J. R. Schuerman

ISBN 10: 9400966636 / ISBN 13: 9789400966635

Published by Springer Netherlands, Springer Netherlands, 2011

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Research and evaluation in the human services usually involves a relatively large number of variables. We are interested in phenomena that have many aspects and many causes. The techniques needed to deal with many variables go beyond those of introductory statistics. Elementary procedures in statistics are limited in usefulness to situations in which we have two or three variables. When we have more than that, application of elementary techniques will often yield mis leading results. Why are elementary techniques inadequate when applied to many variables Why, for example, should we not simply interpret a series of correlations of independent and dependent variables The answer lies in the fact that these correlations are not independent pieces of information. The correlations of vari ables x and z with yare affected by the association of x with z. Hence, talk about the 'effect' of x on y will be somewhat ambiguous, since we will be in cluding in that effect some of the effects of z. We would like to be able to sort out these effects. This is the problem of 'estimation,' that is, estimating the relationships or effects between variables, taking into account their relationships with other variables.

Seller Inventory # 9789400966635

Bibliographic Details

• Title: Multivariate Analysis in the Human Services
• Publisher: Springer Netherlands, Springer Netherlands
• Publication Date: 2011
• Language: English
• ISBN 10: 9400966636
• ISBN 13: 9789400966635
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 16D millimeters 235 millimeters width by 155 millimeters height by 16 millimeters depth
• Weight: 446 grams

About this title

Synopsis

Research and evaluation in the human services usually involves a relatively large number of variables. We are interested in phenomena that have many aspects and many causes. The techniques needed to deal with many variables go beyond those of introductory statistics. Elementary procedures in statistics are limited in usefulness to situations in which we have two or three variables. When we have more than that, application of elementary techniques will often yield mis­ leading results. Why are elementary techniques inadequate when applied to many variables? Why, for example, should we not simply interpret a series of correlations of independent and dependent variables? The answer lies in the fact that these correlations are not independent pieces of information. The correlations of vari­ ables x and z with yare affected by the association of x with z. Hence, talk about the "effect" of x on y will be somewhat ambiguous, since we will be in­ cluding in that effect some of the effects of z. We would like to be able to sort out these effects. This is the problem of "estimation," that is, estimating the relationships or effects between variables, taking into account their relationships with other variables.