HA535 Data Analytics for Health Care Managers - Units 1-4 Flashcards

1
Q

What consists of the amalgamation of research evidence, experience, expertise, and patient preferences in the process of clinical patient care?

A

Evidence-based practice (EBP)

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2
Q

When is evidence-based practice prompted in a clinical care setting?

A

When patients ask questions about their care, diagnostics, certain therapies, drugs, etc.

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3
Q

What is the first step in EBP?

A

Asking clinical questions to familiarize the attending professional with the patient.

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4
Q

What consists of the most optimal outcome in the patient’s care process and overall quality of life?

A

Clinician collected experience

Patients describing personal values and past encounters

Clinically relevant research that has been proven with comprehensive methodology

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5
Q

What acronym is useful in acquiring a well built and comprehensive literature search to identify all potentially relevant scientific articles which are then evaluated for the compatibility and relevance to the patient’s case?

A

The PICO concept

Population/Patient/Problem, Intervention(s), Comparison, and Outcome.

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6
Q

What is clinical significance?

What is statistical significance?

A

Clinical significance requires a sizable change in the patient’s condition. It prioritizes judgement rather than statistics, such that relevant studies can be determined statistically significant but clinically insignificant.

Statistical significance is powered by a large number of observations and oftentimes produces only a trivial amount of noteworthy outcomes.

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7
Q

What is a collection of reports on the treatment of a single patient and have minimal statistical validity, given its lack of comparison between control groups and its general understanding of the question?

A

Case series/case reports

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8
Q

What types of studies should be reviewed when addressing diagnostic questions?

A

Gold standard or cross-sectional studies.

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9
Q

What types of studies should be reviewed when addressing therapy questions?

A

Controlled clinical trials, and then cohort studies in that order. Answers to questions such as cost and potential harms.

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10
Q

What types of studies should be reviewed when addressing prognosis and etiology of the disease?

A

Cohort studies, followed by case controls and case series.

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11
Q

Organize the following from the most general to the most isolated and concentrated ideas.

Case control studies

Randomized control trial

Animal Research

Meta-analysis

Case series/case reports

Systematic review

Cohort studies

A

Animal Research

Case series/case reports

Case control studies

Cohort studies

Randomized control trial

Systematic review

Meta-analysis

Food for thought - Primary literature should be the focus, while secondary sources offer assessments of original studies

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12
Q

What is the most specified of study designs, have thoroughly examined numerous validated studies and have combined the most statistically viable results to elaborate a cause-and-effect relationship between varying treatments and the resulting effects on patient conditions?

A

Meta-analysis

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13
Q

How is EBP used in areas other than clinical care?

A

Creation of policy and guidelines.

All in all, EBP generates a holistic approach towards treatment and recovery that balances general best practices with individualized care.

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14
Q

What are the two dominant research paradigms or methodologies used in human and social sciences?

A

Quantitative and qualitative research.

They are both modes of inquiry that use different methods to acquire answers to social phenomena.

There has been a growth in the mixing of quantitative and qualitative approaches in the twenty-first century, as researchers look to all available research techniques to address the research questions,
rather than promote a preconceived bias toward one methodology or another (Sechrest &
Sidani, 1995). This is referred to a a mixed methods design.

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15
Q

What is the difference between purists and pragmatists in regard to research design and implementation?

A

Purists advocate a mono-method, a single approach to research while pragmatists advocate to integrating multiple methods within a single study and the strengths of both methodologies can be utilized.

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16
Q

What is quantitative research often called?

A

Traditional, positivist, experimental, or empiricist paradigm.

To a positivist researcher, reality is objective and independent of the researcher. Research is
formal, value-free, and unbiased.

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17
Q

What is critical for all research?

A

Accuracy or validity, and consistency or reliability.

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18
Q

What type of research involves measuring subjects and reporting the results?

A

Quantitative research. Experiments test the cause and effect of the sample population.

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19
Q

What are the two quantitative methodologies?

A

Experiment and survey.

The process itself is deductive in nature, with a cause-effect approach
to the research. The researcher generalizes, leading to predictions, explanations, and
understandings

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20
Q

What allows the researcher to generalize the findings of a study to an entire population after the researcher has designed or used a data instrument to collect data?

A

Random sampling.

For those instruments used in other studies, the researcher will need permission and established instruments for data collection should have established validity and reliability.

Creswell (1994) states that “during an experiment, a researcher makes
observations or obtains measures by using instruments at a pre-test and post-test stage”. Researchers create treatment conditions and develop a step-by-step procedure for
conducting the experiment.

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21
Q

Once a study outlines the selection of subjects, how many will participate in the experiment, what happens next?

A

The research states how the random sample will be selected.

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22
Q

What is a variable that is identified as treatment conditions or factors in an experiment?

A

Independent variable.

Examples (very small sample of all that exist)

  • Biological events (such as food deprivation);
  • Social environments;
  • Hereditary factors;
  • Previous training and experience; and
  • Maturity.
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23
Q

What are the four qualitative research designs that are frequently found in human and social science research?

A

Ethnographies

Grounded theory

Case studies

Phenomenological studies

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24
Q

What are the responses or the criterion variables presumed to be “caused” or influenced by the independent variable?

A

Dependent variable.

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25
Q

What research is based on a constructivist or naturalist approach and began as a countermovement to the positivist paradigm where, to the researcher, reality is subjective and seen through the eyes of the participants of the study?

A

Qualitative research.

The process is inductive in nature, and patterns or theories are developed through the research process.

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26
Q

Match the definition to its study.

A Ethnographies

B Grounded theory

C Case studies

D Phenomenological studies

1 This is when the researcher explores a single phenomena that occurs during a defined time or activity and collects data.

2 This is when the researcher examines a human experience through detailed descriptions

3 This is when a researcher studies a cultural group in a natural setting during a specified period of time

4 This is when a researcher develops a theory through multiple stages of data collection and compares it with other theories found in the literature.

A

A3
B4
C1
D2

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27
Q

Identify the Perceived differences as Quantitative or Qualitative [Information]

1 Quantitative researchers view causal relationships among social phenomena from a
mechanistic perspective, while qualitative researchers assign human intentions a major role
in explaining causal relationships among social phenomena.

2 Quantitative researchers assume an objective social reality, whereas qualitative researchers
assume that social reality is constructed by the participants.

3 Quantitative researchers assume that social reality is relatively constant across time and
settings, whereas qualitative researchers assume that social reality is continuously
constructed in social situations.

4 Quantitative researchers take an objective, detached stance towards research participants
and their setting, whereas qualitative researchers become personally involved with research
participants.

5 Quantitative researchers study populations or samples that represent populations, while
qualitative researchers study cases.

6 Quantitative researchers study behavior and other observable phenomena, while
qualitative researchers study the meanings that individuals create and other internal
phenomena.

7 Quantitative researchers study human behavior in natural or contrived settings, while
qualitative researchers study human actions in natural settings.

8 Quantitative researchers use preconceived concepts and theories to determine what data
will be collected, while qualitative researchers discover concepts and theories after data have
been collected.

9 Quantitative researchers generate numerical data to represent the social environment,
while qualitative researchers generate verbal and pictorial data to represent the social
environment.

10 Quantitative researchers use statistical methods to analyze data, whereas qualitative
researchers use analytic induction to analyze data.

11 Quantitative researchers study human behavior in natural or contrived settings, while
qualitative researchers study human actions in natural settings.

12 Quantitative researchers use statistical inference procedures to generalize findings from a
sample to a defined population, whereas qualitative researchers generalize case findings by
searching for other similar cases.

13 Quantitative researchers prepare impersonal, objective reports of research findings, while
qualitative researchers prepare interpretative reports reflecting researchers’ constructions of
the data and an awareness that readers will form their own constructions from what is
reported (Gall, Borg, & Gall, 1996, p. 30).

A

Combining the Two Methods [Information]

Mixing of quantitative and qualitative methodologies is a possibility in any
given study.

Involve the use of observation to address research questions. Both methodologies
“describe their data, construct explanatory arguments from their data and speculate about
why the outcomes they observed happened as they did” (Sechrest & Sidani, 1995, p. 78)

  • Use techniques that are relatively analogous at some level of specificity, such as
    triangulation.
  • Try to discover meaning from the interpretation of data.
  • Use analytical techniques in an attempt to explain complex relationships in the social
    science world (Dzurec & Abraham, 1993; Sechrest & Sidani, 1995).
  • Utilize techniques to verify their data.
  • Use data reduction as an important part of the data analysis process.
  • Promote the role of theory by testing theory (quantitative methods) or initiating and
    building theory (qualitative methods).
  • Can use the same collection of data to get results (Onwuegbuzie & Leech, 2005, p. 380).
    There has been a growth in the mixing of quantitative and qualitative approaches in the
    twenty-first century, as researchers look to all available research techniques to address the
    research questions, rather than promote a preconceived bias toward one methodology or
    another
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28
Q

What is an exemplary manuscript and what does it include? (Strong Characteristics)

A
  • One-third introduction and literature review that includes complex and important topics
    facing scholars and policymakers and the state of current knowledge about those topics,
  • One-third research procedures and findings, which includes the sampling design, research
    design, measurement, statistics, and the proper reporting of research evidence obtained,
    and,
  • One-third discussion and implications, which encompasses synthesis and integration of
    findings obtained from the present investigation within the context of existing knowledge
    (Smart, 2005, p. 463).
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29
Q

What is a literature review?

A

A literature review is a review of the literature that informs the research project.

The literature review presents a theoretical background and a review of other studies that are
closely related to the study that the researcher is developing; makes connections to the
dialogue about the topic that may be appearing in literature; provides a framework for the
researcher’s study; and acts as a benchmark for findings that the research will reveal

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30
Q

Verification of Data

Both quantitative and qualitative data can be verified, using different techniques.
Quantitative research can be verified “through a control process and random sampling
techniques to maximize internal and external validity” (Onwuegbuzie & Leech, 2005, p. 380).
Qualitative verification methodologies include:
* Triangulation;
* Prolonged engagement;
* Persistent observation;
* Leaving an audit trail;
* Member checking;
* Weighing the evidence;
* Checking for representativeness of sources of data;
* Checking for researcher effect;
* Making contrasts and comparisons;
* Checking the meaning of outliers;
* Using extreme cases;
* Ruling out spurious relations;
* Replicating a finding;
* Assessing rival explanations;
* Looking for negative evidence;
* Obtaining feedback from informants;
* Peer debriefing;
* Clarifying researcher bias; and
* Thick description (Creswell, 1998; Onwuegbuzie & Leech, 2005, p. 380).

A

N/A

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31
Q

Typical Qualitative Research Project Format (Informational)

Vivar, McQueen, Whyte, and Armayor (2007) outline the steps that a researcher may take in
developing a qualitative research project. These steps include:
* Selecting an interesting topic;
* Conducting a literature review to identify what has already been written about the topic,
including
* The description of practice-based research, systematic reviews, literature reviews, and metaanalysis;
* Presenting the significance of the study by clarifying why the research is important, through
the writing of a proposal;
* Defining the concepts in the study;
* Finding a theoretical framework;
* Choosing a method of data collection, whether these be interviews, focus groups, and/or
observations;
* Planning the data collection, including running a pilot study to prevent unexpected
problems and to
* Identify modifications necessary in the full study;
* Describing the procedures of data analysis, with a justification of procedures to be used in
the study;
* Enhancing the quality of the study, including presenting an in-depth description of the
project, how and
* What decisions are made and any issues that occur throughout the study;
* Reporting the ethical issues; including potential risks;
* Illuminating the limitations of the study;
* Disseminating the findings, by sharing the results of the research with other professionals
through
* Presenting in professional academic journals, conferences, seminars, and other meetings
where
* Professionals gather in conversation about research;
* Planning the timeframe, or the time it takes to complete the study;
* Concluding, highlighting the major elements of the study; and, finally,
* Presenting the references, or the bibliography.

A

Typical Quantitative Research Project Format (Informational)

Creswell (1994) outlines a typical quantitative research project format, including the following
segments:
* Introduction:
* Context (Statement of the problem)
* Purpose of the study
* Research questions or objectives or hypothesis
* Theoretical perspective
* Definition of terms
* Delimitations and limitations of the study
* Significance of the study
* Review of the Literature:
* Methods:
* Research design
* Sample, population, or subjects
* Instrumentation and materials
* Variables in the study
* Data analysis
* Appendices:
* Instruments

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32
Q

What is the viewpoint of absence of sound theory?

A

Some researchers believe modern research lacks sound theory and does not significantly
contribute to the field of knowledge. Smart (2005), for example, asserts that “reliance on
strong theories is a rare attribute of higher education research manuscripts.” He states that
“the focus seems to be more toward development of our own distinct intellectual heritage
and less toward reliance on the intellectual traditions of the more mature and advanced
academic disciplines” (p. 468).

He mentions three benefits to including sound theory in any research. Sound theories:

  • Provide a roadmap by identifying the important variables to be included in studies and the
    hypothesized relationships among those variables;
  • Incorporate extant empirical findings within a logical and consistent framework; and,
  • Offer a coherent potential answer to important issues facing the academic community (p.
    467).
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33
Q
A
34
Q

What are the advantages of pragmatic research?

A

Advantages of Pragmatic Research
Onwuegbuzie and Leech (2005) state that there are definite advantages to becoming a
pragmatic researcher as opposed to a researcher who is wedded to either quantitative or
qualitative research. They state that pragmatists who use a dual approach to research:
* Are flexible in their investigative techniques, as they attempt to address a range of research
questions that arise;
* Promote collaboration among researchers;
* View research as a holistic endeavor;
* Can use quantitative research to inform qualitative research, and vice versa;
* Can combine macro and micro approaches to viewing data;
* Can merge two voices, the researcher and the participant (p. 383).

35
Q

What does EBM require the integration of?

A

Best research evidence, clinical expertise, and the patient’s unique values and circumstances.

36
Q

Why are traditional sources of information from textbooks, experts, didactic medical education, and medical journals inadequate for EBM?

A

Because they are out of date, frequently wrong, ineffective, or too overwhelming in their volume and too variable to their validity for practical clinical use.

37
Q

What are the two principles of EBM?

A

Hierarchy of evidence and insufficiency of evidence alone

38
Q

What is the hierarchy of evidence and how is it ordered?

A

It is the hierarchy of evidence available that is used in clinical decision making and listed on its likelihood of freedom from error and strength.

Meta-analyses of well conducted large RCTs
Large multi-centric randomized trials
Meta-analyses of well conducted small randomized trials
Single centered randomized trials
Observational studies
Clinical experience or basic science research

39
Q

What is the term used to describe evidence to make health policy and management decisions for populations?

A

Evidence-based health care (EBHC)

40
Q

Why is the need and demand for EBHC growing rapidly? (3 factors)

A

Because of the following factors:

Information overload
Rising patient expectations
Introduction of new technologies and ageing populations

In the past, health care managers tended to focus on cost and quality, thus “doing things right” and leaving “doing the right things” to other forces and chance.

This situation is rapidly changing and everyone involved in decision making must use evidence to enable them to make decisions about “doing the right things”

These skills are necessary for provision of health care in the 21st century. In situations where there is poor quality evidence, the decision maker will have to depend on his experience, available resources and patients expectations and values.

41
Q

Review - What is required to make clinical decisions?

A

Evidence, experience and expertise, and expectations.

42
Q

What is in the scope of evidence-based health care?

A

Producing evidence (research)
Making evidence available especially at point of care, or the value of the new evidence can never be realized
Evidence obtained can be used in two ways: firstly to improve clinical practice and
secondly to improve health service management.

Evidence-based clinical Practice

One of the strategies used to implement this is the Physician-Patient Partnership Program
(PPPP), which is based on the concept of patientcentred care and the idea of the physician and the
patient being partners in problem solving.

Evidence-based policy making, purchasing, and management for health services

Decision makers and managers who are responsible for health care have to make policy decisions
in order to allocate funds, purchase or manage resources. With increasing demand and limited resources these decisions will have to be based on evidence.

43
Q

What skills are required of a practicing evidence based practitioner?

A

See photo.

44
Q

What are the four distinct phases of a systemic process for searching for evidence?

A

Preparation and planning, searching the literature, going beyond the literature, and pulling it all together.

45
Q

What model specifies the learning and understanding of EBP and is selected because it simply and parsimoniously “organizes both old and new concepts of improving care into a whole and provides a framework with which to organize EBP processes and approaches?”

A

ACE Star Model of Knowledge Transformation

The first star point, Discovery, represents the stage wherein new knowledge is generated. The knowledge is in the form of individual or primary research reports and in this form can be found in research journals, abstracts and/or conference proceedings. Kirchhoff (2009) referred to knowledge from a single or individual research study as a “brick” that when added to other “bricks”
(e.g., other single studies) will be transformed into a wall of evidence.

Evidence summary is the second star point, wherein the individual studies, that is, knowledge in the discovery form, are transformed through evidence synthesis and/or meta-analysis into a meaningful statement. This knowledge transformation is conducted by experts in their respective fields and the statements produced are often packaged as a systematic review.

Translation is the third star point, wherein the synthesized knowledge of multiple systematic reviews is transformed in an evidence-based clinical practice guideline (CPG). In this stage of the model, our knowledge is transformed into a very user-friendly form for practice. Evidence-base CPG generally contains an evidence rating for each intervention listed. The most comprehensive set of open access CPGs, most of which are evidence-based, can be found via the National Guideline Clearinghouse, under the auspices of the Agency for Healthcare Research and Quality (AHRQ) of the U.S. Department of Health and Human Services.

The fourth star point is Integration, wherein our knowledge has been transformed to the point at which it is usable by all clinicians and disseminated throughout our institutions. Frequently, systemwide change in practice is difficult, even change based on the best evidence and in the best possible form is difficult. Efforts to overcome barriers to EBP continue to be the focus of many
outcomes by researchers.

The last star point is Evaluation, wherein knowledge in the form we are using is evaluated from the perspective of its impact on outcomes. Possible EBP outcomes at this stage include patient satisfaction, safety, efficacy, efficiency, and health status of whole populations. Evaluation knowledge directs further issues to be researched in Discovery, and the cycle continues as knowledge is
transformed into usable evidence at each star point.

46
Q

What is a data set?

A

Collection of the data of individual cases or subjects.

Usually it is meaningless to present such data individually because that will not produce any important conclusions.

47
Q

What is the science of collection, analysis, presentation, and interpretation of the data, and has two main branches which are what?

A

Statistics. Providing summary statistics of data sets present in a easily absorbable form for the audience.

Descriptive and inferential statistics.

48
Q

Why are summary or descriptive statistics used?

A

To summarize a set of observations, in order to communicate the largest amount of information as simply as possible.

49
Q

What type of statistics draw conclusions from data that are subject to random variation (e.g., observational errors and sampling variation)?

A

Inferential statistics.

In these statistics, most predictions are for the future and generalizations about a population by studying a smaller sample.

50
Q

How do you draw inference from study participants in terms of different groups?

A

You use statistical methods have assumptions including normality of the continuous data like numerical and visual methods (which have their pros and cons).

Descriptive and inferential statistics both are employed in scientific analysis of data and are equally important in the statistics.

51
Q

What are the three major types of descriptive statistics?

A

Measures of frequency (frequency, percent), measures of central tendency (mean, median, and mode), and measures of dispersion or variation (variance, SD, standard error, quartile, interquartile range, percentile, range, and coefficient of variation (CV)), provide simple summaries about the sample and the measures.

52
Q

Why are the measures of central tendency also called measures of the first order?

A

Because it helps in further statistical analysis because many techniques like correlation, t-test, ANOVA test are calculated using values of measures of central tendency.

A representative value (measures of central tendency) is considered good when it was calculated using ALL observations and not affected by extreme values because these values are used to calculate for further measures.

53
Q

For measures of central tendency, what phrases belong to which tendency?

Mathematical average?

Positional average?

Maximum frequency?

A

Mean, median, and mode.

54
Q

What descriptive statistics give us an idea about homogeneity or heterogeneity of the data and is quantitatively the degree of variation of values in a population or sample?

A

Measures of Dispersion like variance, SD, standard error, quartile, interquartile range, percentile, range, and CV.

55
Q

Measure of Dispersion

What does standard deviation measure? Why is it called standard deviation?

A

It measures how spread out values is from its mean value.

Called SD because we have taken a standard value (mean) to measure the dispersion.

56
Q

What are the two ways in which variables are classified?

A

A variable can collect either qualitative or quantitative data.

A variable differing in quantity is called a quantitative variable (e.g., weight of a group of patients), whereas a variable differing in quality is called a qualitative variable (e.g., the Fitzpatrick skin type)

57
Q

What is a simple test you can do to differentiate between qualitative and quantitative variables?

A

The subtraction test.

if you can subtract one variable to another and get a meaningful result, then you are dealing with a quantitative variable.

58
Q

What are the two forms of quantitative variables?

A

Discrete or continuous.

Discrete variables are variables in which no values may be assumed between the two given values (e.g., number of lesions in each patient in a sample of patients with urticaria).

Continuous variables can take any value in between the two given values (e.g., duration for which the wheals (hives) last in the same sample of patients with urticaria).

59
Q

What test can you do to differentiate between continuous and discrete variables?

think number of occasions of hives vs the time taken for hives to subside.

A

Use the “mid-way” test.

If, , for every pair of values of variable, a value exactly mid-way between them is meaningful, the variable is continuous.

60
Q

Under the umbrella of qualitative variables, what are the different variables?

A

Nominal/categorical and ordinal variables.

61
Q

What are variables which can be slotted into different categories like gender or type of psoriasis?

A

Nominal/categorical variables. (Qualitative)

62
Q

What are variables that are similar to categorical, but they can be put into an order (e.g., a scale for severity of itching)?

A

Ordinal/ranked variables (Qualitative)

63
Q

What is another name for dependent and independent variables in an experimental study?

What is the third variable?

A

Dependent variable is known as the outcome variable and is linked to the primary outcome of the study.

The independent variable is also known as the explanatory variable and is something which is not affected by the experiment itself but which can be manipulated to affect the dependent variable.

Confounding variables are extra variables, which can have an effect on the experiment and can cause spurious associations. Moisturizer use during an experimental study on a topical ointment for psoriasis may be a confounding variable.

64
Q

[Review] What are descriptive and inferential statistics?

A

Descriptive statistics give a summary about the sample being studied without drawing any inferences based on probability theory. These will always be needed even if inferential statistics are the goal. To make these statistics inferential, it would involve a specific statistical test, like the mann-whitney u-test, to compare the mean scores.

65
Q

If we describe population using tools such as frequency distribution tables, percentages, and other measures like central tendency like the mean, what type of statistics are we referring to?

A

Descriptive statistics.

These can help in summarizing data in the form of simple quantitative measures such as percentages or means or in the form of visual summaries such as histograms and box plots.

66
Q

In descriptive statistics, what does univariate, bivariate, and multivariate analysis mean?

A

They are statistics used to describe a single variable, two variables, or multiple variables.

67
Q

What can descriptive statistics be broadly put under in two categories?

A

Sorting/grouping (frequency distribution tables, like a stem and leaf diagram) and illustrations/visual displays

Summary statistics

68
Q

What are the most common tools used for visual display of discrete and continuous variables?

What about comparing variables?

A

Frequency diagrams, bar charts (for discrete variables) and histograms (for continuous variables)

Composite bar charts (see image)

Pie charts help show how total quantity is divided among its constituent variables.

Scatter diagrams can be used to illustrate the relationship between two variables. (see image)

69
Q

What are the main tools used for summary statistics? 2

A

Measures of central tendency and measures of dispersion and variation.

70
Q

[Review] What are mean, median, mode again?

A

Mean is the average of the data and can be skewed by outliers. The median is better to use since it divides the data set into equal halves, which is referred to as the 50th percentile (50% of the values are above it and 50% of the values are below it).

In data sets with equal numbers, you take an average of the two values.

The mode is the most common data point and this may or may not necessarily be in the center of the distribution.

71
Q

Why is the median the best measure of central tendency from among the mean, median, and the mode?

A

In a symmetric distribution, all three are the same, whereas in skewed data the median and mean are not the same; lie more toward the skew, with the mean lying further to the skew compared with the median. See picture for example.

72
Q

What is a measure of dispersion that gives the spread between the lowest and highest values?

A

The range.

Ex. 86 - 30 = 56 (range)

73
Q

The interquartile range is a measure of dispersion that is more valuable than range because it is not affected by the extreme values of the data set.

What is a quartile?

And how is interquartile determined?

A

A quartile is one of the values which break the distribution into four equal parts.

The 25th percentile is the data point which divides the group between the first one-fourth and the last three-fourth of the data. The first one-fourth will form the first quartile.

The 75th percentile is the data point which divides the distribution into a first three-fourth and last one-fourth (the last one-fourth being the fourth quartile).

The range between the 25th percentile and 75th percentile is called the interquartile range.

74
Q

What is a measure of dispersion that are it becomes larger, the further the individual units are from the mean?

How is it calculated?

A

Variance.

Subtracting each individual value from the mean and then adding them and finding the average would give a clue to the total dispersion, but the problem is that since the deviations are a mix of negative and positive values, the final total becomes zero.

To calculate variance, this problem is overcome by adding squares of the deviations. So variance would be the sum of squares of the variation divided by the total number in the population (for a sample we use “n-1”). If we were to divide by n alone, we would always underestimate variance, and if we divided by n-2, we would always over estimate. N-1 is best for variance calculation.

To get a more realistic value of the average dispersion, we take the square root of the variance, which is called the “standard deviation.”

Standard deviation is the spread of a group of numbers from the mean.

The variance measures the average degree to which each point differs from the mean.

While standard deviation is the square root of the variance, variance is the average of the squared difference of each data point from the mean.

Example:

For a class of students, the scores are 85, 90, 88, 92, and 82. To calculate the variance and standard deviation, find the mean: (85 + 90 + 88 + 92 + 82) / 5 = 87.4. Then, calculate the variance: [(85-87.4)^2 + (90-87.4)^2 + (88-87.4)^2 + (92-87.4)^2 + (82-87.4)^2] / 5 = 64.8 / 5 = 12.96. Finally, calculate the standard deviation, which is the square root of the variance: Standard Deviation = √12.96 ≈ 3.60.

75
Q

What is a box plot?

A

It is a composite representation that portrays the mean, median, and mode, and the outliers.

76
Q

What measures the symmetry of distribution?

For example, distribution curves can be symmetric where they look the same on both sides of a central point.

Also, what is kurtosis? This involves “tails”.

A

The concept of skewness and when a distro curve is not symmetrical, it is considered skewed.

Kurtosis is a representation of outliers. Distributions with high kurtosis tend to have heavy tails indicating a larger number of outliers, whereas distributions with low kurtosis have light tails, indicating lesser outliers.

There are formulas to calculate both skewness and kurtosis.

77
Q

What do you call all units of a particular population under study?

A

A census.

If you had all units, that’d be great but it is unrealistic. Having all samples would remove chances of sampling error (difference between the outcome characteristics in a random sample when compared with the true population values - something that is virtually unavoidable when you take a random sample).

78
Q

What is a subset of the population to reach a conclusion?

A

Sample size.

To have sufficient numbers, having a bigger sample size rather than a smaller one is needed to make a meaningful and accurate conclusions and reduce the effect of sampling error.

79
Q

What are the two types of broad sampling?

What are the subtypes of sampling under these two main types?

A

Probability and nonprobability sampling.

For probability sampling, we have:
Simple random sampling (each member in a population has an equal chance of being selected)

Stratified random sampling (in nonhomogeneous populations, the population is divided into subgroups - followed by random sampling in each subgroup)

Systemic sampling (sampling is based on a systemic technique - e.g., every third person is selected for a survey)

Cluster sampling (similar to stratified sampling except the clusters here are preexisting clusters unlike stratified sampling where the researcher decides on the stratification criteria)

Nonprobability sampling is where every unit in the population does not have an equal chance of inclusion into the sample. These methods include:

Convenience sampling (e.g., sample selected based on ease of access)

Purposive sampling (where only people who meet specific criteria are included in the sample)

80
Q

Why is getting an accurate calculation and calculation much in advance of sample size an essential aspect of good study design?

A

A sample size that is too less may make the study underpowered, whereas a sample size which is more than necessary might lead to a wastage of resources.

81
Q

Sample Size Calculation Practice (for a randomized control trial)

Identify important factors such as:

Study design

Type of statistical test

Level of significance

Power and effect size

Variance (standard deviation for quantitative data)

Expected proportions in the case of qualitative data (based on previous data either based on previous studies or based on the clinicians’ experience)
- A pilot study may be needed in order to help generate this data for further studies based on a larger sample size

It is also important to know whether the data follow a normal distribution or not.

A

N/A