PR 2| WEEK 3-4 Flashcards

1
Q
  • examines the effects of an intervention on an outcome of interest.
    o The primary purpose of intervention research is to engender a desirable outcome for
    individuals in need (e.g., reduce depressive symptoms or strengthen reading skills)
A

Intervention research

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2
Q

where the goal is to prevent a negative outcome from occurring.

A

Prevention research

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3
Q

where the goal is often to support specific tenets of theoretical paradigms.

A

 Classic laboratory experimentation

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4
Q

Assessment of an intervention’s effects, the sine qua non of intervention research, varies according to study design, but typically involves both ____________________________.

A

statistical and logical inferences

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5
Q

There are many ways of letting a variable, factor, or condition intervene or have an application
on the subjects, and of later determining the effects of such intervention (TREATMENT).
Here are some of these methods: (De Mey 2013; Creswell 2013)

A
  1. treatment evaluation;
    2 pre-test and post-test of multiple treatments or conditions
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6
Q

There are two types of intervention studies:

A
  1. randomized controlled trials
  2. non-randomized or quasi-experimental trials.
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7
Q

is considered to be the gold standard of clinical research because it is the only known
way to avoid selection and confounding biases.
 It approximates the controlled experiment of basic science.

A

Randomized controlled trial

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8
Q

apply the conclusions of the experiment to people in the general population.

A

aim of a trial

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9
Q

Three phases of Data Collection Procedure

A

before
during
after

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10
Q

1.Develop your data collection instruments and materials.
2.Seek permission from the authorities and heads of the institutions or communities where you will conduct your study.
3.Select and screen the population using appropriate sampling techniques.
4.Train the raters, observers, experimenters, assistants, and other research personnel who may be involved in
data gathering.
5.Obtain informed consent from the subjects.
6.Pilot-test the instruments to determine to determine potential problems that may occur when they are administered.

A

Before

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11
Q

1.Provide instructions to the participants and explain how the data will be collected.
2.Administer the instruments, and implement the intervention or treatment, if applicable.
3.Triangulation technique enhanced validation of data using two or more sources and methods

A

During

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12
Q

1.Immediately encode or transcribe and archive your data.
2.Safeguard the confidentiality of your data.
3.Later, examine and analyze your data using the appropriate statistical tools.

A

 After

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13
Q

Before you begin collecting data, you need to consider:

A

 The aim of the research
 The type of data that you will collect
 The methods and procedures you will use to collect, store, and process the data
To collect high-quality data that is relevant to your purposes, follow these four steps.

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14
Q

4 steps to collect high-quality data that is relevant to your purposes

A

Step 1: Define the aim of your research
Step 2: Choose your data collection method
Step 3: Plan your data collection procedure
Step 4: Collect the data

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15
Q

is expressed in numbers and graphs and is analyzed through statistical methods

A

Quantitative Data

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16
Q

expressed in words and analyzed through interpretations and categorizations

A

qualitative data

17
Q

is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in
making more effective decisions, especially in the context of quantitative research.

A

Statistics

18
Q

methods of organizing, summarizing, and presenting data in an informative way e.g. via various charts, tables, and infographics.

A

. Descriptive Statistic

19
Q

The methods used to estimate a property of a population on the basis of a sample e.g. T-Test, Z-Test, ANOVA, Regression Analysis, Factor Analysis, Cluster Analysis.

A

Inferential Statistics

20
Q

average value, is the most commonly used measure of central tendency.
 The measure is used to estimate the unknown population mean when the data have been collected
using an interval or ratio scale
 The data should display some central tendency, with most of the responses distributed around the
mean

A

a. Mean

21
Q

is the value that occurs most frequently
 It represents the highest peak of the distribution
 The mode is a good measure of location when the variable is inherently categorical or has otherwise

A

b. Mode

22
Q

is the middle value when the data are arranged in
ascending or descending order
 If the number of data points is even, the median is usually estimated as the midpoint
between the two middle values by adding the two middle values and dividing their sum
by 2

A

c. Median

23
Q

measures the spread of the data
Simply the difference between largest and smallest values in the sample

A

a. Range

24
Q

The difference between the mean and an observed value is called the deviation from the mean. The variance is the mean squared deviation from the mean.

A

b. Variance

25
Q

– square root of the variance.
It‟s also a measure of how spread the values are

A

c. Standard Deviation

26
Q

– is the ratio of the standard deviation to the mean expressed as
percentage, and it is a unitless measure of relative variability,

A

d. Coefficient of variation

27
Q

– is simply a statement that something is true.
 It is a tentative, a claim or an assertion about people, objects, or events.

A

Hypothesis

28
Q

is a procedure in making decisions based on a sample evidence or probability theory used
to determine whether the hypothesis is accepted or rejected.

A

Hypothesis Testing

29
Q

is a hypothesis of no difference and it‟s denoted by Ho
 The null hypothesis can be expressed in statement from stating no significant difference
between the variables compared or using,

A

A. Null hypothesis

30
Q

 Alternative hypothesis is a hypothesis to be considered as an alternate to the null
hypothesis. It is usually denoted by

A

B. Alternative Hypothesis

31
Q

Steps in Hypothesis Testing

A
  1. Formulate the null and alternative hypothesis
  2. Decide the level of significance
  3. Choose appropriate test statistic
  4. Establish the critical Region/Compute the Value of the Statistical Test
  5. Make a Decision