NSE212 final

What is degrees of freedom?

-based on or depends on the sample size
-formula is different for each statistical test
-important for determining statistical significance of tests

df for central tendency

N-2

df for independent t-test

n1-1 + n2-1 OR total # of subjects - 2

df for dependent t-test (paired t-test)

n-1

df ANOVA

between groups (# of groups - 1) divided by within groups (total sample - # of groups)

df one-sample chi-square

of rows - 1

df two-sample chi-square

(# of rows - 1) x (# of colomns - 1)

df Pearson's r

N-2

Strong relationship correlation coefficient

0.5-1.0

moderate-strong correlation coefficient

0.4

moderate correlation coefficient

0.3

weak-moderate correlation coefficient

0.2

weak - no relationship correlation coefficient

0-0.1

what is 1 SD in a normal distribution

34.13

what is between 1-2 SD in a normal distribution

13.59

what is between 2-3 SD in a normal distribution

2.15

what is 3 SD in a normal distribution?

0.13

what is it called when you reject the null when it is true?

type 1 error

reject the null when it is false?

correct

accept the null when it is true?

correct

accept the null when it is false?

type 2 error

if P is less than alpha 0.05

reject the null hypothesis because it is statistically significant (this is the goal of researchers)

if P is greater than alpha 0.05

accept the null hypothesis because it is not statistically significant

when is a two-tailed test used

non-directional hypothesis

when is one-tailed test used

directional hypothesis

what is a between-subjects comparioson?

different subjects are compared

what is a within-subjects comparison?

same subjects compared more than once

what are the characteristics of experimental designs?

-control: introduction of one or more constants
-randomization/random assignment: equal chance of people being assigned to either control or experimental group
-manipulation

advantages and disadvantages of experimental designs?

advantages:
-tests cause and effect
-the highest level of evidence
disadvantages:
-participants drop out
-testing effects

explain the 2 types of experimental designs

1. true experimental (pre-post test control group): measuring effects before and after treatment of control and experimental group

2. after only (post-test only): measuring only after treatment of control and experimental group

how is quasi different from an experimental design?

random assignment is not used and control is not fully possible due to the nature of the IV or participants. still tests cause and effect but the confidence in making causal relations are weak

nonequivalent control group design (quasi)

measuring before and after treatment of both experimental and control group

after-only nonequivalent control group design

measuring only after treatment of both experimental and control group

one-group (pretest-posttest design)

measuring before and after treatment of experimental group only

time-series design

measuring data of intervention group only before treatment and after treatment at 1 week, 2 weeks, etc

advantages and disadvantages of quasi designs

advantages: more feasible
disadvantages: difficult to make clear cause and effect statements, threats to internal validity

how is a nonexperimental design different from experimental and quasi?

-explores people, places, events as they naturally occur so NO INTERVENTION/TX FROM RESEARCHER
-not looking at cause and effect but rather RELATIONSHIPS/DIFFERENCES
-IV occurs naturally and the researcher CANNOT MANIPULATE
-no randomization

correlational studies

-nonexperimental (relationships/differences studies)
-examines the relationship between 2 or more variables NOT cause and effect
-tests if variables covary (as one variable changes, does a related change occur in the other variable?)
-interested in the strength of the relationship between variables

cross-sectional studies

-nonexperimental (developmental studies)
-examine data at ONE TIME/OCCASION with SAME PARTICIPANTS

longitudinal/prospective studies

-nonexperimental (developmental studies)
-collects data from the SAME group at DIFFERENT TIMES
-by collecting data at yearly intervals, the researcher obtains a longitudinal perspective

retrospective/ex post facto studies

-nonexperimental (developmental studies)
-from after the fact
-DV already affected by IV so the investigator attempts to link current events to past events
-researcher hypothesizes that variable X (smoking) is linked to variable Y (lung cancer)

nonexperimental design advantages and disadvantages

-unable to explain cause and effect
-useful in making predictions
-important when randomization, control or manipulation is not possible

survey studies

-nonexperimental
-classified as descriptive, exploratory, comparative
-useful for gaining lots of information from a large population
-data tends to be superficial

name and explain other types of designs

-methodological: evaluation of data-collection instruments
-systematic review/meta-analysis: summation of research studies based on a focused question and a meta-analysis is a systematic summary using statistical techniques to assess
-secondary analysis: form of research where previously collected and analyzed data is used for a different purpose
-epidemiological studies: factors affecting the health and illness of a population are examined in relation to the environment
-clinical practice guidelines: link research and practice and serve as a guide for HCPs

what affects control?

-homogenous sampling
-consistency in data collection
-manipulation of the IV
-randomization

what are threats to internal validity?

-makes it unknown if it is the IV that caused the DV
-history
-maturation
-testing effects
-instrumentation
-mortality
-selection bias

what are threats to external validity?

-concerns the generalizability of findings to additional populations
-internal validity must first be established
-selection effects: researcher cannot obtain ideal sample)
-reactive effects: participants responses to being studied
-measurement effects

what is nonprobability sampling?

-no randomization in selecting this sample
-convenience: most readily accessible persons (first 50 patients admitted into a hospital)
-quota: subjects who meet the inclusion criteria are recruited and consecutively enrolled until the total sample size is reached

probability sampling

-representative group
-simple random
-stratified random
-multistage (cluster)
-systematic

simple random sampling

-researcher establishes sampling frame (list from which a sample is taken)
-people in a course listed and random participants are chosen from that list

stratified random sampling

-population is divided into strata
-participants randomly selected from each strata

multistage (cluster) sampling

-random sampling of units that meet eligibility criteria
-from large to small
-first stage: all hospitals in Canada
-second stage: all ICUs in each of those selected hospitals
-third stage: sampling nurses full time in those units

systematic sampling

-involves the selection of an interval at which point individual participants are selected

what is a power analysis?

used to see how large a sample should be to show statistical significance

what are the 2 elements of data quality?

1. rigour: we want high quality measurement instruments that reflect the concepts being studied (trustworthiness)

2. psychometric assessments: detects evidence on quality of measurement tools which include: -reliability (consistency) -validity (accuracy)

what is reliability and its 3 aspects?

-test to which an instrument yields the same results repeatedly
-stability, internal consistency, equivalence

stability

-test-retest reliability: does the instrument produce the same results repeatedly?
-however participants may recognize repeated items

internal consistency

-homogeneity: do items measure the same concept?
-need to have multiple items to establish internal consistency
-Chronbach's alpha: closer to 1 is high internal consistency but greater than 0.7 is acceptable (ranges from 0-1)

equivalence

-interrater reliability: will the tool produce the same results when equivalent procedures are used? refers to consistency of observations between 2 or more observers with the same measurement tool
-tend to do with observational methods
intrarater reliability: 1 observer observes the same behavior several times

what is validity and its kinds?

-does instrument measure what it intends to measure? (accuracy)
-concept validity, criterion-related validity, construct validity

concept validity

-determines if the measurement tool and the items represent the content desired
-content validity index: experts rate items 1-4 if they are relevant

criterion-related validity

-measures the relation between scores from the instrument with external criteria
-predictive validity: degree of correlation between the measure of concept and a future measure of the same concept (do high school grades predict post-secondary grades?)
concurrent validity: degree of correlation of 2 measures of the same construct administered at the same time (pulse oximeter vs. ABGs-gold standard)

construct validity

-extent to which a test measures a theoretical construct or trait
-complex process

levels of measurement

-nominal: dichotomous or categorical, mutually exclusive (pick one only), numbers assigned have no meaning, mode and bar graph used as measure of central tendency
-ordinal: categorical, mutually exclusive, numbers assigned have meaning, distance between categories is unknown, mode, median, and bar graphs can be used
-interval: variables are continuous and rank ordered, equal intervals between numbers, 0 does not mean absence, can report mean, median, mode and histograms
ratio: variables continuous and rank ordered, have a meaningful 0 and means the absence, can also report mean, median, mode, and histograms

what are the measures of central tendency?

mean, median, mode

what are the measures of variability?

-range: h-l
-standard deviation: how much each score deviates from the mean
-variance: spread of data (SD squared)

describe a positively skewed distribution

-the mean is greater than the median and mode
-the peak is to the left while it tails off to the right

describe a negatively skewed distribution

-the mean is lower than the median and mode
-the peak is to the right while it tails off to the left

what is rxy?

-the correlation between X and Y (correlation coefficient)
-ranges from -1.00 to +1.00
-how the value of one variable changes in relation to changes in another variable

positive/direct correlation

both variables go in the same direction

negative/indirect correlation

as one variable goes in one direction, the other variable goes in a different direction

what is the coefficient of determination?

r2 or the correlation coefficient squared

what are assumptions for a parametric test?

-DV is interval or ratio level
-variances are homogenous
-normal distribution
-sample data is usually more than 30
-t-test, ANOVA, Pearson's r

what are t-tests and what are the types? (2)

-compare DIFFERENCES between group means
-t-test for independent groups
-t-test for dependent groups (paired t-test)

describe the t-test for independent groups

-test DIFFERENCES not relationships
-compares means between TWO GROUPS ONLY
-participants tested only once and are different people in each group (experimental vs. control group)
-IV is at the nominal level
-DV is at the interval or ratio level

describe the t-test for dependent groups (paired t-test)

-compare mean scores
-for one group of people who are tested TWICE (within group design)
-tested before and after an intervention
-used in pre-test-post-test studies

what is the ANOVA?

-helps decide if the difference in group means is related to the IV or due to other reasons
-breaks total variability in a dependent variable into 2 parts:
variability between the groups and variability within groups

what is the rule for variability and ANOVA?

if the variability BETWEEN (numerator) groups is significantly greater than the variability WITHIN (denominator) groups, then the probability is high that the IV led to differences in group means -- reject the null

between-groups variability

-d/t general differences between the groups
-measures how much difference exists between groups`

within-groups variability

-variability within each group

what is the test statistic for ANOVA?

-F ratio
-Post hoc test will be done if F ratio results are statistically significant

what are the types of ANOVA? (4)

1. one-way/simple ANOVA

2. two-way/multifactor ANOVA

3. repeated measures ANOVA (RMANOVA)

4. multivariate statistical analysis of covariance (ANCOVA)

what is a one-way/simple ANOVA?

-tests differences between MORE THAN 2 GROUPs of treatment (IV)
-ex: DV is tumour size and the IV is the treatment which consists of 3 groups (chemo, radiation, both)
-participants tested only once
-non-directional F test
-participants in each group are different people

what is a multifactor/two-way ANOVA? (factorial analysis of variance)

-same as one-way ANOVA but has more than 1 IV
-ex: testing the impact of exercise and diet on weight loss with students

what is repeated measures ANOVA? (RMANOVA)

-participants tested MORE THAN ONCE or at different points in time (before/during/after intervention)
-can be one-way or two-way ANOVA

what is a multivariate statistical analysis of covariance? (ANCOVA)

-used to statistically control the effect of extraneous variables on DV
-tests the significance of differences between group means after adjusting scores on the DV to eliminate the effect of covariates
-used when control through randomization is lacking

what is a chi-square test and its types? (2)

-a non-parametric test
-involves a comparison of what is observed and what is expected by chance
-one-sample chi-square test (goodness of fit) and two-sample chi-square test (test for independence)

what is a one-sample chi square test?

-tests the difference in the proportion of only 1 variable
-ex: what is the proportion of RNs who smoke, do not smoke, and never smoked? (1 variable of smoking status)

what is a two-sample chi-square test?

-tests the difference in the proportion between 2 variables
-ex: is there an association between exercise patterns and smoking status in RNs? (first variable is exercise and second variable is smoking)

when do you use Pearson's r?

-testing RELATIONSHIPS between 2 variables
-tests the degree to which variables are related
-by squaring correlation coefficient, you can determine the amount of variance