3.3 Framing Mixed
Method by Grounded theory

Grounded theory forms
the based line of qualitative research which is inductive in nature. It tends
to progress from inductive through different methods and stages. Likewise
grounded theory could also actualize its aims with the introduction of
deductive method to conceptualized its framing from none participant
observation to theoretical content. This style of research methodology could
fit in the mixed method to actualize its aim. Just like grounded theory the
mixed methods using both inductive and deductive methods in its researcher
method, the inductive method is qualitative methods and the deductive methods
is quantitative methods. Inductive promotes an unintentional observation that
is, the openness of the researcher to discovery, usually from observation and
experiences from communication with the people, culture and the environment that
will guide the conceptualization of new ideals which forms theories. The
deductive research could be applied depending on the nature of the project
begin carried. In some case the researcher need to make use of already existing
information or data which helps to randomized the sample into a frame for
analysis.

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Mixed method has
procedures like the grounded theories, which can go from abstract to none
abstract vice versa (Driscoll et. al 2007). But grounded theory is more
particular about the none abstract way of researching issues which tend to
portrait a none bias way of research. When using mixed methods, it always tends
to qualify the quantitative aspect by drawing logical reasoning from the
ethnography of the study which is analyzed in comparison to the quantitative
information. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

4.0
Delineate Mixed Method Framed in Grounded Theories from other Methods

A study using grounded
theory gives a series a rules and procedures which is likely to begin with a
question, or even just with the collection of qualitative data. As researchers
review the data collected; repeated ideas, concepts or elements become
apparent, and are tagged with codes, which have been extracted from the data. This
give the research work a much more robust fact from subjective statement to
objectiveness facts. The outcome can be framed within the qualitative methods
like in the social science and humanities or in quantitative frame such as the
natural and the physical science for quantifying reasoning.

Mixed methods is a more
rigorous process both in its qualitative and quantitative methods, it takes a
detailed account. It brings interplay of both the qualitative and the
quantitative perspective to research style moving from co-mixed within method
or a co-switch between methods at different levels or stages. It is a dynamic
method which helps in flexible evaluation to outcome and impact analysis
irrespective of lay down theories which reduces research bias to the nearest
minimum. It gives a new inspired thought of reasoning to fresh ideals in
research, taking away the stereotype to research methods   

These categories may
become the basis for new theory. Thus, mixed method framed in grounded theory
is quite different from the traditional model of research, where the researcher
chooses an existing theoretical framework, and only then collects data to show
how the theory does or does not apply to the phenomenon under study.

 

 

 

 

 

 

 

 

 

 

 

 

5.0
Advantages and Disadvantages of Mixed Method

5.1
Advantages

Mixed method (MM) are
used in the validation of the data collected using both qualitative and quantitative
methods, the variability in the data collection leads to a greater validity in
the result or outcome, it gives a broader horizon into the research project.

Mixed method (MM)
answer questions from of multiple perspective that is, from qualitative to
quantitative, brings both inductive and deductive reasoning into play. It give
room to question like what, why, how, and if. It creates flexibility within and
between its contexts.

Mixed method tries to
close the gaps or lags both in content and context of the data collected, it
ensure that the data of analysis is robust for a broader explanation or
in-depth coverage  of the outcome or
impact analysis.

Mixed methods is
dynamic in its evaluation processes, ensure to curb and manage the researcher
per-existing assumptions about a researcher area, problem or issues. It tends
to validate the researchers un-biasness from its inductive method allowing
openness to fresh ideas.

Mixed method is both
supplementary and complimentary in research work. When one method does not
provided sufficient information to the analysis or research work.

Mixed method is good
for data transformation, it can be used to transform qualitative data to
quantitative and vice versa.

5.2
Disadvantages

The conversion of
qualitative data to quantitative data often leads to the loss of its
flexibility and depth, which are the main advantages to qualitative research.
This loss occurs because qualitative coding is multidimensional (Bazeley,
2004). Quantitative coding are fixed in a single dimension, sometimes
dichotomous.

Mixed method design is
vulnerable to collinearity or multi-collinearity, this results from the
qualitative data begin quantitized (Roberts 2002).When researcher try to put
the data into categories to enable coding of the data collineartiy occurs. The controlling
for collinearity by the researcher reduces the validity of the Information
provided. Mixed method is expensive to conduct and it is time consuming. It is
also difficult to find a researcher with adequate experience in both QUANT AND
QUAL research methods. Another issue in mixed methods is how to interpret
conflicting results from both QUANT and QUAL analysis.

 

6.0 Assessing Mixed
Methods for Development Studies

MM is a very important
tool in research design for development planners and policy makers. MM gives a
deeper insight to the issues or projects by describing and analysis the facts
as related to individuals, groups, societies, and their sociological backgrounds.
It’s a good tool of policy advocacy for implementation, because MM examines
quantitative result and describes its facts in the simplest term to the policy
developers, backing up the narrative discourse with data presented in
percentages, frequency of occurrences and averages.

Most recently, MM is a
power tool for recent fields of study such as monitoring and evaluation of
programs and projects. Development itself is an evolutionary subject matter,
with dynamic issues. In the same way the development researcher and planners
tends to monitor the progress made at every given stage of the project because
of its constant changes. MM impact assessment helps researcher and development
planners to see the corresponding changes at different stage of the project
which aids clarity. Impact assessment it a vital part of the evaluation
process, it alert the planner on the extent to which the program as affected
the targeted group. These conclusions are usually drawn from the statistical
data or analysis of the data collected.

MM is a good tool for
forecasting and predicting programs and projects and can also assess the
probability of occurrences for changes base on its qualitative processes from
in-depth inductive assessment.