Agriculture Reference
In-Depth Information
help in reducing the blood sugar level, a measur-
able response. In socioeconomic studies, stimulus
variables may be in the form of action variable
like documentary film, field demonstration, and
method demonstration, an effect which would be
measured in the form of adoptions or non-
adoptions of a particular technology in which
documentary/field
characters are designated by different numbers.
As such, quality characters take the values 0, 1, 2,
etc., and are known as dummy variables. Dummy
variables have special implications, particularly
in relational analysis. For example, instead of an
ordinary simple regression analysis in case of
numeric variables, one should go for
probit
,
demonstration/method
logit
regression analysis when
encountered with dummy variables.
, and
nomit
demonstrations were used.
5.1.8 Control Variable
5.1.10 Preference Variable
Control variables are nothing but the independent
variables in relational studies, which can affect
the relationship between the dependent variables
and the independent variables and which could
be controlled by making them constant or by
eliminating them from the model. Thus, control
variables are the type of independent variables
which could be controlled by a researcher to
study effectively the effects of other independent
variables. Thus, independent variable can be
categorized into two groups, that is, the
These are generally discrete type of variables
whose values are either in decreasing or increas-
ing order. For example, in a survey of acceptabil-
ity of a film by the audience, respondents were
asked to grade the film by using five different
codes which are as follows: (1) excellent, 1; (2)
very good, 2; (3) good, 3; (4) poor, 4; and (5) bad,
5. It may be noted here that there is no relation-
ship between the difference in grades 1 and
2 with that of the difference between any two
consecutive grades and vice versa. Similarly, in a
study of constraint analysis, farmers were asked
to indicate the importance of the following
constraints in accordance with their preferences
by using codes from 1 to 8: (1) weather, (2)
finance, (3) irrigation, (4) marketing, (5) price
of input, (6) price of output, (7) nonavailability
of good quality seed, and (8) nonavailability of
appropriate technology. The farmers are to
arrange the above eight constraints from 1 to
8 with 1 being allotted to the most important
constraint and 8 to the least important constraint.
control
variable group
and
the moderator variable
group
. In comparison to the control variable
groups, the effect of moderator variables is stud-
ied, keeping the control variables at constant or
eliminating or minimizing them. Depending
upon the objective of a research, it is up to a
researcher to determine the moderator variables
and the control variables.
5.1.9 Dummy Variable
In many research studies, particularly concerned
with the qualitative characters, it is very difficult
to guide/put a study under mathematical treat-
ment. To overcome this problem, one of the
techniques is to assign numbers against the qual-
ity parameters. For example, in a study
concerned with gender-related issues, the male
may be assigned number 1, while 0 for the
female or vice versa. In a study of plant type, a
bushy type of plants may be assigned number 1,
erect type number 2, and tree type number 3, and
so on. Thus, in each of the above cases, quality
5.1.11 Multiple Response Variable
In multiple response variables, a variable can
assume more than one value. In a social, eco-
nomic, market research, etc., it becomes very dif-
ficult for respondents to select a particular option
against the other alternatives; rather, they opt for
combinations of absence; a typical example is the
use of modern-day high-tech mobile phones. If a
respondent is asked to indicate the purposes of
using mobile phones in his/her daily life, the
