advance research

1. ir. PANCHITO M. LABAY
FORD Fellow, Professor 5

2. What are variables?
--building blocks of quantitative methods
--concepts that can be measured by indicators. Indicators can be
numerical values or categories
--can be unidimensional (e.g. age), multidimensional (e.g.
intelligence) or dichotomous (e.g. gender)
--can be dependent (DV) or effect or outcome variable and the other
one is independent (IV) or the causal variable
Ex. Some theorists found out that longevity can be measured with
the following indicators: sex, education, income, occupation, etc.
The latter indicators are the independent variables or causal
variables, which can bring changes to longevity (DV) or outcome
variable.

3. --can be mediating or intervening or go-between variable which
affects the test result of the dependent variable
--can be moderator variable that affects the relationships between
DV and IV at different levels
--can be extraneous variable which compete with the independent
variable in explaining the outcome
--can be confounding variable if the extraneous variable is really
proven as the cause of the outcome
Ex. Amount of studying (IV) leads to input of knowledge in long-term memory
(mediating variable), which affects test results (DV)
Ex. The relationship between the amount of studying (IV) and test results (DV)
changes at different levels with the use of memory-enhancing drug
(moderator)

4.  Survey Research
 Experimental Research
• Pre-Experimental
• True Experimental
• Quasi-Experimental
 Correlational Studies
What are the types of Quantitative
Research?

5.  Surveys represent one of the most
common types of quantitative, social
science research. In survey research, the
researcher selects a sample of
respondents from a population and
administers a standardized questionnaire
to them.
Survey Research

6.  The questionnaire, or survey, can be a written document
that is completed by the person being surveyed,
-an online questionnaire,
-a face-to-face interview, or
-a telephone interview.
 Using surveys, it is possible to collect data from large or
small populations (sometimes referred to as the universe
of a study).
 Different types of surveys are actually composed of
several research techniques, developed by a variety of
disciplines. For instance, interview began as a tool
primarily for psychologists and anthropologists, while
sampling got its start in the field of agricultural
economics (Angus and Katona, 1953, p. 15).

7. What are the types experimental research?
• True experimental design
--randomisation of participants (subjects e.g. pupils) from a population
(e.g. Grade IV) to form the sample (N) for the experiment
--manipulation by having experimental groups and control or
comparison groups that the treatment will be applied
--random assignment of treatment to groups
• Quasi-experimental design
--there is randomisation of participants from a population but
restricted to pre-assigned groups
--manipulation with the presence of control groups
--random assignment of treatment to groups when possible
• Pre-experimental design
--no randomnisation of participants from a population
--presence of control group in some cases, but usually not
--no random assignment of treatment to groups

8. Example of Pre-experimental designs are some of the ‘investigatory
projects’ in Science of the students. It may or may not have a control
group and no randomnisation of participants from a population.
Example: One-group pretest posttest design: Measuring the effectivity of
teaching method A in increasing the pupils’ level of understanding
concepts in science
1. Advertises for volunteer or participants for the experiment or handpicks
students
2. Administers a pretest to measure strength
3. Exposes the subjects to the hypothesised teaching method that will
improve the students level of understanding
4. Administers the posttest

9. Example of experimental design
Example: Pretest posttest control group design: Measuring the effectivity of
teaching method A in increasing the pupils’ level of understanding
concepts in science
Group 1 (Exptal group) Pretest Treatment Posttest
Group 2 (Control grp) Pretest No-treatment Posttest
1. Randomly assign the participants to the experimental or the control
groups
2. Administers a pretest to each group on the dependent variable
3. Apply the treatment to the experimental group (Group 1). In Group 2 what
can be applied is the traditional method
4. Administers the posttest to both groups
Note: This design is not limited only to two groups

10. Example of experimental design using the Solomon four group design
Example: Pretest posttest control group design: Measuring the effectivity of
teaching method A in increasing the pupils’ level of understanding
concepts in science
Group 1 (Exptal group) Pretest Treatment Posttest
Group 2 (Control grp) Pretest No treatment Posttest
Group 3 (Control grp) No pretest Treatment Posttest
Group 4 (Control grp) No pretest No treatment Posttest
1. Randomly assign the participants to the experimental or the control
groups
2. Administers a pretest to each group on the dependent variable
3. Apply the treatment to the experimental group (Group 1). In Group 2 what
can be applied is the traditional method
4. Administers the posttest to both groups

11. Quasi-Experimental Design
Nonequivalent Comparison-Group Design
This is a design that contains a treatment group and a
nonequivalent untreated comparison group about of which
are administered pretest and posttest measures. The groups
are “nonequivalent” because you lack random assignment.
Because of the lack of random assignment, there is no
assurance that the groups are highly are similar at the
outset of the study.
• Because there is no random assignment to groups,
confounding variables (rather than the independent variable)
may explain any difference observed between the
experimental and control groups.

12. Correlational Research
 A correlation is simply defined as a relationship
between two variables. The whole purpose of
using correlations in research is to figure out
which variables are connected.
 Positive correlations mean that as variable A
increases, so does variable B.
 A negative correlation is defined as when
variable A increases, variable B will decrease.

13. Example of Correlational Study
pH
soil
moist.
(v/v)
soil
temp.oC
soil org.
C (µg/g)
avail.
P(µg/g)
avail.
N(µg/g)
# mycor.
spores/g
soil
H'
pH 1
soil moisture 0.391lc 1
soil temp. -0.235lc -0.987*** 1
soil organic C 0.284lc 0.995*** -0.998*** 1
avail. P 0.739** 0.909*** -0.829*** 0.856*** 1
avail. N 0.956*** 0.102nc 0.062nc -0.012nc 0.507* 1
# mycr. spores/g soil 0.651** 0.953*** -0.891*** 0.912*** 0.993*** 0.399lc 1
H' -0.122nc 0.866*** -0.936*** 0.917*** 0.579* -0.409lc 0.674** 1
Correlation of the measured pH, soil moisture, soil organism, etc..
Scale: 0.81 - 1.00 = high or strongly correlated (***), 0.61 - 0.80 = substantially
correlated (**), 0.41 - 0.60 = moderately correlated (*), 0.21 - 0.40 = low correlation
(lc), 0.01 - 0.20 = negligible or no correlation (nc)
Family Income Average Grades
Family Income 1
Average Grades -0.1653444 nc 1
Correlation between family income and the students’ grades.

14.  They are used to determine the extent to which
two or more variables are related among a
single group of people (although sometimes
each pair of score does not come from one
person…the correlation between the teacher’s
performance and the pupils’ performance).
 There is no attempt to manipulate the variables
(random variables)
When are correlation methods used?

15. Thank you again folks!