D514 Analytical Methods of Healthcare
Leaders study guide with complete
solution
ANOVA test - ANS Analysis of variance (ANOVA) may be used in research studies
where there are two or more groups to compare.
Chi-square tests - ANS Chi-square tests determine if an association exists between
two categorical variables.
Control group - ANS In a healthcare environment, this group of patients does not
receive the treatment that is being studied.
Experimental group - ANS This group of patients receives the treatment being studied
with follow-up observation to determine the effect of the treatment.
F-test - ANS The F-test is designed to test if two population variances are equal. The
ratio of the two variances is compared. If they are equal, the ratio of the variances will
be 1.
Frequency - ANS Frequencies measure how often a particular value occurs to assess
the importance of a value or check the variation of the values in a study.
Hypothesis - ANS A proposed explanation for an observation that leads to a prediction.
Through investigation and the use of statistical data, those doing the study will either
confirm or reject the hypothesis. Testing the hypothesis will show if there is a link (or
not) between two or more variables.
Integrity - ANS Research always makes some assumptions, depending on the type of
method used. Research assumptions must be identified to determine possible breaches
of integrity.
,Interval data - ANS Interval data includes units of equal size, such as IQ results. There
is no zero point. An example of interval scale is time: Time is measured in 24 hours in
each day; the time between each hour is the same, 60 minutes.
Mean - ANS Mean is the arithmetic average. Divide the sum of all scores by the total
number of scores.
Median - ANS Median is the midpoint of the distribution of values, or the point above or
below which 50 percent of the values fall.
Methods section components - ANS When analyzing the quality of a study, a careful
evaluation of the research methods can reveal critical details about population and
sample, covariables and hypothesis, data presentation, statistical analysis, and study
limitations.
Misleading statistics - ANS Interpreting and presenting the results of data analysis
affords many opportunities for accidental or deliberate misrepresentations of data.
Common examples include implying causation, extrapolating beyond the reasonable,
relying on a biased or incomplete sample, and using inappropriate graphical
representations.
Mode - ANS Mode is the value that occurs most frequently in the data.
Multivariate regression analyses - ANS Multivariate regression analyses can be used
to analyze and adjust risk. This analysis model contrasts each measured factor to the
patient's risk of a particular outcome.
Nominal data - ANS Nominal data can be measured as a frequency or percentage,
and the mean of these data cannot be calculated. Nominal data in healthcare might
include demographic information about patients. The word nominal means "pertaining to
a name."
Ordinal data - ANS Ordinal data can be measured as a frequency, and the mean of
ordinal data is often calculated. Ordinal data in healthcare might include patient
satisfaction surveys using a Likert scale. The word ordinal means to "put in order."
Parametric and nonparametric tests - ANS Parametric tests are based on probability
distributions. Nonparametric tests are used when data are not normally distributed.
, Pearson's correlation - ANS Pearson's correlation is used with interval and ordinal
scale data and determines the extent to which a change in one variable tends to be
associated with a change in another.
Qualitative research methods - ANS Qualitative research is aimed at understanding
perceptions, perspectives, interpretations, and opinions. Qualitative research methods
often include questionnaires, interviews, written documents, observations, and focus
groups.
Ratio data - ANS Divide one quantity by another, and you have a value. You will have
a proportion, a percentage or a rate.
Reliability, validity, and analysis of questionnaires - ANS Questionnaires can be
evaluated for reliability based on their consistency (stability) or repeatability over time;
questionnaires are valid if they measure or record what they purport to measure. Data
from questionnaires may then be grouped according to nominal, ordinal, or interval or
ratio data.
Research - ANS Research can inform decisions regarding the development and
efficacy of new processes, systems, technologies, environments, and organizational
structures to support operations.
Research platform - ANS Research is built on a platform of previous knowledge, the
scientific method.
Risk adjustment - ANS Risk adjustment is essential for comparing data across
systems, especially among patients with varying comorbid diseases and complex
treatment modalities. Multivariate regression analyses can be used to analyze and
adjust risk. This analysis model looks at each measured factor to the patient's risk of a
particular outcome.
Risk of error and harm - ANS Studies should include an analysis of any sources of
error as well as a thorough explanation of the consequences associated with a
particular study treatment.
Sample size - ANS The design of the study provides insight into an appropriate
number and volume of each variable. The calculation of statistical confidence factors
informs the validity testing of the study sample size.
Leaders study guide with complete
solution
ANOVA test - ANS Analysis of variance (ANOVA) may be used in research studies
where there are two or more groups to compare.
Chi-square tests - ANS Chi-square tests determine if an association exists between
two categorical variables.
Control group - ANS In a healthcare environment, this group of patients does not
receive the treatment that is being studied.
Experimental group - ANS This group of patients receives the treatment being studied
with follow-up observation to determine the effect of the treatment.
F-test - ANS The F-test is designed to test if two population variances are equal. The
ratio of the two variances is compared. If they are equal, the ratio of the variances will
be 1.
Frequency - ANS Frequencies measure how often a particular value occurs to assess
the importance of a value or check the variation of the values in a study.
Hypothesis - ANS A proposed explanation for an observation that leads to a prediction.
Through investigation and the use of statistical data, those doing the study will either
confirm or reject the hypothesis. Testing the hypothesis will show if there is a link (or
not) between two or more variables.
Integrity - ANS Research always makes some assumptions, depending on the type of
method used. Research assumptions must be identified to determine possible breaches
of integrity.
,Interval data - ANS Interval data includes units of equal size, such as IQ results. There
is no zero point. An example of interval scale is time: Time is measured in 24 hours in
each day; the time between each hour is the same, 60 minutes.
Mean - ANS Mean is the arithmetic average. Divide the sum of all scores by the total
number of scores.
Median - ANS Median is the midpoint of the distribution of values, or the point above or
below which 50 percent of the values fall.
Methods section components - ANS When analyzing the quality of a study, a careful
evaluation of the research methods can reveal critical details about population and
sample, covariables and hypothesis, data presentation, statistical analysis, and study
limitations.
Misleading statistics - ANS Interpreting and presenting the results of data analysis
affords many opportunities for accidental or deliberate misrepresentations of data.
Common examples include implying causation, extrapolating beyond the reasonable,
relying on a biased or incomplete sample, and using inappropriate graphical
representations.
Mode - ANS Mode is the value that occurs most frequently in the data.
Multivariate regression analyses - ANS Multivariate regression analyses can be used
to analyze and adjust risk. This analysis model contrasts each measured factor to the
patient's risk of a particular outcome.
Nominal data - ANS Nominal data can be measured as a frequency or percentage,
and the mean of these data cannot be calculated. Nominal data in healthcare might
include demographic information about patients. The word nominal means "pertaining to
a name."
Ordinal data - ANS Ordinal data can be measured as a frequency, and the mean of
ordinal data is often calculated. Ordinal data in healthcare might include patient
satisfaction surveys using a Likert scale. The word ordinal means to "put in order."
Parametric and nonparametric tests - ANS Parametric tests are based on probability
distributions. Nonparametric tests are used when data are not normally distributed.
, Pearson's correlation - ANS Pearson's correlation is used with interval and ordinal
scale data and determines the extent to which a change in one variable tends to be
associated with a change in another.
Qualitative research methods - ANS Qualitative research is aimed at understanding
perceptions, perspectives, interpretations, and opinions. Qualitative research methods
often include questionnaires, interviews, written documents, observations, and focus
groups.
Ratio data - ANS Divide one quantity by another, and you have a value. You will have
a proportion, a percentage or a rate.
Reliability, validity, and analysis of questionnaires - ANS Questionnaires can be
evaluated for reliability based on their consistency (stability) or repeatability over time;
questionnaires are valid if they measure or record what they purport to measure. Data
from questionnaires may then be grouped according to nominal, ordinal, or interval or
ratio data.
Research - ANS Research can inform decisions regarding the development and
efficacy of new processes, systems, technologies, environments, and organizational
structures to support operations.
Research platform - ANS Research is built on a platform of previous knowledge, the
scientific method.
Risk adjustment - ANS Risk adjustment is essential for comparing data across
systems, especially among patients with varying comorbid diseases and complex
treatment modalities. Multivariate regression analyses can be used to analyze and
adjust risk. This analysis model looks at each measured factor to the patient's risk of a
particular outcome.
Risk of error and harm - ANS Studies should include an analysis of any sources of
error as well as a thorough explanation of the consequences associated with a
particular study treatment.
Sample size - ANS The design of the study provides insight into an appropriate
number and volume of each variable. The calculation of statistical confidence factors
informs the validity testing of the study sample size.
