Difference between revisions of "SOCR Data NIPS InfantVitK ShotData"

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(Created page with '== SOCR Data - SOCR Body Density Data == ==Summary== This is a comprehensive dataset that lists estimates of the percentage of body fat determined by underwater weighing and…')
 
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== [[SOCR Data]] - SOCR Body Density Data ==
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== [[SOCR Data]] - SOCR Neonate Infant Pain Score (NIPS) Data (Vitamin K shots) ==
  
 
==Summary==
 
==Summary==
This is a comprehensive dataset that lists estimates of the percentage of body fat determined by underwater weighing and various body circumference measurements for 252 men.
+
These data include 79 babies (infants) in a control group (NC) and 79 babies in the intervention (Interv) group. The '''intervention''' group babies were held by their mothers prior to, and during the administering of the shot -- “Kangaroo Care”.  NIPS scores were recorded immediately after the shot was administered, after 30 seconds, one minute, and two minutes.
 +
 
 +
==Background==
 +
Nurses at [http://www.northbay.org/ Northbay Healthcare] participate in an Evidence Based Practice (EBP) program.  The purpose of EBP is to research and implement improvements in nursing care, and then to gauge the success these changes using statistical methods.  In one study, they introduced changes in the way newborn babies are handled. The goal is to reduce pain experienced by the infants resulting from their [http://en.wikipedia.org/wiki/Vitamin_K vitamin K] shot.  Supervising nurses assessed a newborn's pain using a scale known as a [http://www.anes.ucla.edu/pdf/assessment_tool-nips.pdf Neonatal Infant Pain Score (NIPS)].  NIPS scores range from 0 to 7, and are obtained by observing the infant's bodily reactions.
  
 
==Classroom use of this data set==
 
==Classroom use of this data set==
 
[[Image:SOCR_Data_Dinov_BMI_062408_Fig1.png|150px|thumbnail|right| [http://www.stat.ucla.edu/%7Edinov/courses_students.dir/07/Fall/STAT13.1.dir/STAT13_notes.dir/BMI_Calculator.html Body Mass Index] ]]
 
[[Image:SOCR_Data_Dinov_BMI_062408_Fig1.png|150px|thumbnail|right| [http://www.stat.ucla.edu/%7Edinov/courses_students.dir/07/Fall/STAT13.1.dir/STAT13_notes.dir/BMI_Calculator.html Body Mass Index] ]]
  
This data set can be used to illustrate multiple regression techniques. Accurate measurement of body fat is inconvenient/costly and it is  desirable to have easy methods of estimating body fat that are cost-effective and convenient.
+
This data set can be used to illustrate (multivariate, logistic) [[SOCR_EduMaterials_AnalysesActivities| regression analyses]], [http://socr.ucla.edu/htmls/ana/ non-parametric tests], and diverse array of [[SOCR_EduMaterials_ChartsActivities|exploratory data analyses]].  
 
 
References to the [http://apps.who.int/bmi/index.jsp BMI index by country/region] and [http://www.fao.org/docrep/004/Y3557E/y3557e13.htm#v per capita food consumption and undernourishment (calories)] may be appropriate when discussing BMI.
 
 
 
==Siri's Equation==
 
A variety of popular health books suggest that the readers assess their health, at least in part, by estimating their percentage of body fat. In Bailey (1994), for instance, the reader can estimate body fat from tables using their age and various skin-fold measurements obtained by using a caliper. Other texts give predictive equations for body fat using body  circumference measurements (e.g. abdominal circumference) and/or skin-fold measurements ([[SOCR_Data_BMI_Regression#References | Behnke and Wilmore, 1974, pp. 66-67; Wilmore, 1976, p. 247; or Katch and McArdle, 1977, pp. 120-132]]).
 
 
 
Percentage of body fat for an individual can be estimated once body density has been determined. Siri (1956) assumes that the body consists of two components - lean body tissue and fat tissue.
 
* Suppose we let:
 
** ''D'' = Body Density (gm/cm<sup>3</sup>)
 
** ''A'' = proportion of lean body tissue
 
** ''B'' = proportion of fat tissue (A+B=1)
 
** ''a'' = density of lean body tissue (gm/cm<sup>3</sup>)
 
** ''b'' = density of fat tissue (gm/cm<sup>3</sup>)
 
*Then, we have <math>D = {1 \over {A \over a} + {B\over b}}</math> and solving for ''B'' we find
 
<math>B = {1\over D}\times{a b\over a-b} - {b\over a-b}</math>. Using the estimates ''a=1.10 gm/cm<sup>3</sup>'' and ''b=0.90 gm/cm<sup>3</sup>'' ([[SOCR_Data_BMI_Regression#References | Katch and McArdle, 1977, p. 111 or Wilmore, 1976, p. 123]]) we come up with '''Siri's equation''': Percentage of Body Fat <math>PBF = 100\times B = {495\over D} - 450</math>.
 
 
 
==Estimation of Body Density (BD)==
 
Volume, and hence body density, can be accurately measured a variety of ways. The technique of underwater weighing ''computes body volume as the difference
 
between body weight measured in air and weight measured during water
 
submersion. In other words, body volume is equal to the loss of weight in
 
water with the appropriate temperature correction for the water's density'' (Katch and McArdle, 1977, p. 113). Using this technique, <math>BD = {WA\over {WA-WW\over CF} - LV}</math>, where
 
* ''WA'' = Weight in air (kg)
 
* ''WW'' = Weight in water (kg)
 
* ''CF'' = Water correction factor. CF=1 at 4<sup>o</sup> C (Celsius) as one-gram of water occupies exactly one cm<sup>3</sup> of space, and CF=0.997 at 25<sup>o</sup> C)
 
* ''LV'' = Residual Lung Volume (liters) [[SOCR_Data_BMI_Regression#References | Katch and McArdle (1977), p. 115]].
 
Other methods of determining body volume are given in [[SOCR_Data_BMI_Regression#References | Behnke and Wilmore, 1974, p. 22]].
 
 
 
==BMI Calculators==
 
There are many body-mass-index calculators. Here are some examples:
 
* [http://www.stat.ucla.edu/%7Edinov/courses_students.dir/07/Fall/STAT13.1.dir/STAT13_notes.dir/BMI_Calculator.html This BMI calculator] allows data in various formats and includes interpretations of the results.
 
* [http://www.nutritiondata.com/tools/calories-burned This is a complex BMI calculator that also computes your daily burned calories (based on your life-style) and estimates your daily calorie intake].
 
  
 
==Data Description==
 
==Data Description==
 
The body density dataset includes the following 15 variables listed from left to right:
 
The body density dataset includes the following 15 variables listed from left to right:
* Density determined from underwater weighing
+
* '''Index''': Index of the observation (random ordering within each group, group 1 followed by group 2)
* Percent body fat from [[SOCR_Data_BMI_Regression#References | Siri's (1956) equation]]
+
* '''Group_NC1_Interv2''': Index of the group: NC=1; Intervention=2
* Age (years)
+
* '''Immediate''': NIPS assessment of pain at time of vitamin K shot (t=0)
* Weight (kg)
+
* '''30_Sec_Later''': NIPS assessment of pain 30 seconds after the vitamin K shot (t=30)
* Height (cm)
+
* '''60_Sec_Later''': NIPS assessment of pain 60 seconds after the vitamin K shot (t=60)
* Neck circumference (cm)
+
* '''120_Sec_Later''': NIPS assessment of pain 120 seconds after the vitamin K shot (t=120)
* Chest circumference (cm)
+
* '''Total_Cry_Time''': The total try time (in seconds)
* Abdomen 2 circumference (cm)
+
* '''Cluster''': This is an automatically derived clustering measure using all variables except Group_NC1_Interv2 and based on [http://factominer.free.fr/ Hierarchical Clustering/FactoMineR algorithm].
* Hip circumference (cm)
 
* Thigh circumference (cm)
 
* Knee circumference (cm)
 
* Ankle circumference (cm)
 
* Biceps (extended) circumference (cm)
 
* Forearm circumference (cm)
 
* Wrist circumference (cm)
 
* '''Notes'''
 
** The measurement standards are listed in Benhke and Wilmore, 1974, pp. 45-48, where, for instance, the abdomen 2 circumference is ''measured laterally, at the level of the iliac crests, and anteriorly, at the umbilicus''.
 
** These data are used to produce the predictive equations for lean body weight given in the abstract ''Generalized body composition prediction equation for men using simple measurement techniques'', K.W. Penrose, A.G. Nelson, A.G. Fisher, FACSM, Human Performance Research Center, Brigham Young University, Provo, Utah  84602 as listed in ''Medicine and Science in Sports and Exercise'', vol. 17, no. 2, April 1985, p. 189.
 
** The predictive equations were obtained from ''training'' data (the first 143 of the 252 cases that are listed in the spreadsheet below). The remaining 109 cases may be used for ''testing''.
 
** These data were generously supplied by Dr. A. Garth Fisher who gave permission to freely distribute the data and use for non-commercial purposes.
 
** The data is also available [http://wiki.stat.ucla.edu/niser/uploads/0/0d/NISER_Data_BMI_Regression_Dataset.pdf in PDF format].
 
** The [http://www.stat.ucla.edu/~dinov/courses_students.dir/07/Fall/STAT13.1.dir/STAT13_notes.dir/BMI_Calculator.html body-mass-index is defined by]: <math>BMI = {Weight(kg)\over Height^2(m)}</math>.
 
  
 
==Data Table==
 
==Data Table==
Line 69: Line 27:
 
{| class="wikitable" style="text-align:center; width:75%" border="1"
 
{| class="wikitable" style="text-align:center; width:75%" border="1"
 
|-
 
|-
 
+
!Index||Group_NC1_Interv2|| Immediate|| 30_Sec_Later||60_Sec_Later||120_Sec_Later||Total_Cry_Time||Cluster
 +
|-
 +
|1||1||6||7||6||2||63||3
 +
|-
 +
|2||1||5||1||2||0||0||3
 +
|-
 +
|3||1||7||6||6||7||54||3
 +
|-
 +
|4||1||3||7||3||0||27||3
 +
|-
 +
|5||1||7||5||6||0||19||3
 +
|-
 +
|6||1||6||6||6||2||2||3
 +
|-
 +
|7||1||7||7||6||0||46||3
 +
|-
 +
|8||1||6||7||0||0||33||3
 +
|-
 +
|9||1||5||0||4||0||56||3
 +
|-
 +
|10||1||7||7||7||6||63||3
 +
|-
 +
|11||1||7||6||2||2||33||3
 +
|-
 +
|12||1||4||4||0||1||19||3
 +
|-
 +
|13||1||7||6||3||0||37||3
 +
|-
 +
|14||1||7||0||4||0||68||3
 +
|-
 +
|15||1||7||6||7||0||73||3
 +
|-
 +
|16||1||7||7||3||4||29||3
 +
|-
 +
|17||1||7||6||6||0||59||3
 +
|-
 +
|18||1||7||3||0||0||20||3
 +
|-
 +
|19||1||7||2||0||0||35||3
 +
|-
 +
|20||1||6||5||7||4||80||3
 +
|-
 +
|21||1||7||0||0||2||20||3
 +
|-
 +
|22||1||7||7||7||7||81||3
 +
|-
 +
|23||1||0||7||0||0||65||1
 +
|-
 +
|24||1||7||0||7||4||46||3
 +
|-
 +
|25||1||7||7||6||0||84||3
 +
|-
 +
|26||1||7||6||0||0||44||3
 +
|-
 +
|27||1||7||7||3||4||23||3
 +
|-
 +
|28||1||7||1||0||0||17||3
 +
|-
 +
|29||1||7||0||1||1||12||3
 +
|-
 +
|30||1||6||5||5||5||33||3
 +
|-
 +
|31||1||7||2||5||6||45||3
 +
|-
 +
|32||1||7||0||0||1||11||3
 +
|-
 +
|33||1||7||4||0||4||12||3
 +
|-
 +
|34||1||4||0||0||0||3||3
 +
|-
 +
|35||1||6||2||7||6||48||3
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|-
 +
|36||1||7||3||0||0||15||3
 +
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 +
|37||1||7||6||5||5||50||3
 +
|-
 +
|38||1||7||3||0||6||22||3
 +
|-
 +
|39||1||7||7||7||7||86||3
 +
|-
 +
|40||1||7||3||3||3||30||3
 +
|-
 +
|41||1||7||7||5||7||73||3
 +
|-
 +
|42||1||6||5||0||0||20||3
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|43||1||7||3||4||0||25||3
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|44||1||7||0||6||6||26||3
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 +
|45||1||6||6||5||0||66||3
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 +
|46||1||7||0||0||0||14||3
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 +
|47||1||7||2||0||0||4||3
 +
|-
 +
|48||1||7||6||6||6||33||3
 +
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 +
|49||1||7||7||7||6||48||3
 +
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 +
|50||1||7||0||1||0||22||3
 +
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 +
|51||1||7||7||7||3||47||3
 +
|-
 +
|52||1||7||3||0||0||14||3
 +
|-
 +
|53||1||5||7||6||0||51||3
 +
|-
 +
|54||1||7||0||0||0||15||3
 +
|-
 +
|55||1||7||3||3||3||37||3
 +
|-
 +
|56||1||5||6||7||4||24||3
 +
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 +
|57||1||7||4||7||3||39||3
 +
|-
 +
|58||1||6||7||7||6||70||3
 +
|-
 +
|59||1||7||2||0||0||48||3
 +
|-
 +
|60||1||7||7||0||5||42||3
 +
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 +
|61||1||7||3||7||1||63||3
 +
|-
 +
|62||1||7||0||3||0||23||3
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 +
|63||1||7||7||6||3||58||3
 +
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 +
|64||1||7||3||0||0||10||3
 +
|-
 +
|65||1||0||0||0||0||0||1
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|66||1||3||0||0||0||0||3
 +
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 +
|67||1||7||7||7||5||73||3
 +
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 +
|68||1||7||7||7||6||39||3
 +
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 +
|69||1||7||7||7||7||54||3
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|70||1||7||2||6||5||52||3
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|71||1||6||4||6||0||39||3
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|72||1||7||7||3||0||61||3
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|73||1||7||3||0||0||34||3
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|74||1||7||7||6||6||30||3
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|75||1||7||7||7||3||100||3
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|76||1||7||6||5||2||55||3
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|-
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|77||1||7||5||4||0||58||3
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|78||1||7||5||5||0||49||3
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|79||1||7||5||2||0||18||3
 +
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|80||2||1||0||0||0||0||1
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|83||2||5||3||4||1||32||2
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|84||2||3||0||0||0||0||1
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|85||2||7||4||1||0||36||2
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|86||2||5||5||1||0||20||2
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|87||2||5||3||4||2||23||2
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|88||2||7||6||3||1||39||2
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|-
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|89||2||1||0||1||1||14||1
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|90||2||7||0||4||4||54||2
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|91||2||4||0||0||0||36||2
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|92||2||2||0||0||0||0||1
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|93||2||7||6||0||6||29||2
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|94||2||7||1||0||1||11||2
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|-
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|95||2||4||0||0||0||5||2
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|-
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|96||2||7||7||5||2||64||2
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|-
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|97||2||7||7||1||2||52||2
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|-
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|98||2||7||7||1||0||19||2
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|-
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|99||2||5||2||2||1||28||2
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|100||2||7||4||0||0||22||2
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|-
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|101||2||7||7||6||0||68||2
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|-
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|102||2||7||6||0||0||39||2
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|-
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|103||2||7||7||7||0||60||2
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|-
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|104||2||7||7||7||3||78||2
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|-
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|105||2||6||0||0||0||11||2
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|-
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|106||2||7||6||0||0||59||2
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|-
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|107||2||7||4||4||0||28||2
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|-
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|108||2||7||7||7||1||64||2
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|-
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|109||2||7||0||0||0||8||2
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|-
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|110||2||5||0||1||3||64||2
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|-
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|111||2||7||5||7||7||72||2
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|-
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|112||2||4||2||0||2||50||2
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|-
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|113||2||7||6||7||0||44||2
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|-
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|114||2||7||1||0||0||11||2
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|-
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|115||2||7||3||0||0||16||2
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|-
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|116||2||7||0||0||0||30||2
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|-
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|117||2||5||4||5||0||14||2
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|-
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|118||2||2||7||0||0||10||1|| 
 +
119||2||2||0||0||1||20||1
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|-
 +
|120||2||3||0||0||0||7||1
 +
|-
 +
|121||2||7||2||2||2||10||2
 +
|-
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|122||2||7||6||5||2||58||2
 +
|-
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|123||2||7||1||0||0||19||2
 +
|-
 +
|124||2||2||6||0||1||41||1
 +
|-
 +
|125||2||7||3||0||0||17||2
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|-
 +
|126||2||5||2||2||0||5||2
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|-
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|127||2||7||5||0||2||49||2
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|-
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|128||2||7||2||0||0||36||2
 +
|-
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|129||2||4||0||4||4||73||2
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|-
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|130||2||4||1||0||0||19||2
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|-
 +
|131||2||4||7||3||0||40||2
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|-
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|132||2||7||4||6||1||43||2
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|-
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|133||2||5||0||4||0||22||2
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|-
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|134||2||7||3||1||0||32||2
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|-
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|135||2||7||7||3||0||70||2
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|-
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|136||2||7||5||0||3||35||2
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|-
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|137||2||7||7||5||0||35||2
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|-
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|138||2||7||6||6||0||35||2
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|-
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|139||2||7||0||0||0||8||2
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|-
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|140||2||5||0||0||0||5||2
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|-
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|141||2||7||1||0||0||33||2
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|-
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|142||2||7||7||4||0||46||2
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|-
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|143||2||7||4||0||0||15||2
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|-
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|144||2||5||7||0||0||11||2
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|-
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|145||2||6||0||0||0||9||2
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|-
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|146||2||6||0||0||0||12||2
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|-
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|147||2||7||0||0||0||2||2
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|148||2||7||7||3||0||43||2
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|149||2||7||7||2||2||73||2
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|150||2||7||6||4||0||38||2
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|151||2||7||4||0||0||11||2
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|152||2||7||7||7||3||60||2
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|153||2||7||1||0||0||27||2
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|154||2||7||0||0||0||25||2
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|155||2||6||6||2||0||2||2
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|157||2||1||0||0||0||0||1
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|158||2||2||0||0||0||18||1
 
|}
 
|}
 
</center>
 
</center>

Revision as of 18:21, 10 April 2012

SOCR Data - SOCR Neonate Infant Pain Score (NIPS) Data (Vitamin K shots)

Summary

These data include 79 babies (infants) in a control group (NC) and 79 babies in the intervention (Interv) group. The intervention group babies were held by their mothers prior to, and during the administering of the shot -- “Kangaroo Care”. NIPS scores were recorded immediately after the shot was administered, after 30 seconds, one minute, and two minutes.

Background

Nurses at Northbay Healthcare participate in an Evidence Based Practice (EBP) program. The purpose of EBP is to research and implement improvements in nursing care, and then to gauge the success these changes using statistical methods. In one study, they introduced changes in the way newborn babies are handled. The goal is to reduce pain experienced by the infants resulting from their vitamin K shot. Supervising nurses assessed a newborn's pain using a scale known as a Neonatal Infant Pain Score (NIPS). NIPS scores range from 0 to 7, and are obtained by observing the infant's bodily reactions.

Classroom use of this data set

This data set can be used to illustrate (multivariate, logistic) regression analyses, non-parametric tests, and diverse array of exploratory data analyses.

Data Description

The body density dataset includes the following 15 variables listed from left to right:

  • Index: Index of the observation (random ordering within each group, group 1 followed by group 2)
  • Group_NC1_Interv2: Index of the group: NC=1; Intervention=2
  • Immediate: NIPS assessment of pain at time of vitamin K shot (t=0)
  • 30_Sec_Later: NIPS assessment of pain 30 seconds after the vitamin K shot (t=30)
  • 60_Sec_Later: NIPS assessment of pain 60 seconds after the vitamin K shot (t=60)
  • 120_Sec_Later: NIPS assessment of pain 120 seconds after the vitamin K shot (t=120)
  • Total_Cry_Time: The total try time (in seconds)
  • Cluster: This is an automatically derived clustering measure using all variables except Group_NC1_Interv2 and based on Hierarchical Clustering/FactoMineR algorithm.

Data Table

Index Group_NC1_Interv2 Immediate 30_Sec_Later 60_Sec_Later 120_Sec_Later Total_Cry_Time Cluster
1 1 6 7 6 2 63 3
2 1 5 1 2 0 0 3
3 1 7 6 6 7 54 3
4 1 3 7 3 0 27 3
5 1 7 5 6 0 19 3
6 1 6 6 6 2 2 3
7 1 7 7 6 0 46 3
8 1 6 7 0 0 33 3
9 1 5 0 4 0 56 3
10 1 7 7 7 6 63 3
11 1 7 6 2 2 33 3
12 1 4 4 0 1 19 3
13 1 7 6 3 0 37 3
14 1 7 0 4 0 68 3
15 1 7 6 7 0 73 3
16 1 7 7 3 4 29 3
17 1 7 6 6 0 59 3
18 1 7 3 0 0 20 3
19 1 7 2 0 0 35 3
20 1 6 5 7 4 80 3
21 1 7 0 0 2 20 3
22 1 7 7 7 7 81 3
23 1 0 7 0 0 65 1
24 1 7 0 7 4 46 3
25 1 7 7 6 0 84 3
26 1 7 6 0 0 44 3
27 1 7 7 3 4 23 3
28 1 7 1 0 0 17 3
29 1 7 0 1 1 12 3
30 1 6 5 5 5 33 3
31 1 7 2 5 6 45 3
32 1 7 0 0 1 11 3
33 1 7 4 0 4 12 3
34 1 4 0 0 0 3 3
35 1 6 2 7 6 48 3
36 1 7 3 0 0 15 3
37 1 7 6 5 5 50 3
38 1 7 3 0 6 22 3
39 1 7 7 7 7 86 3
40 1 7 3 3 3 30 3
41 1 7 7 5 7 73 3
42 1 6 5 0 0 20 3
43 1 7 3 4 0 25 3
44 1 7 0 6 6 26 3
45 1 6 6 5 0 66 3
46 1 7 0 0 0 14 3
47 1 7 2 0 0 4 3
48 1 7 6 6 6 33 3
49 1 7 7 7 6 48 3
50 1 7 0 1 0 22 3
51 1 7 7 7 3 47 3
52 1 7 3 0 0 14 3
53 1 5 7 6 0 51 3
54 1 7 0 0 0 15 3
55 1 7 3 3 3 37 3
56 1 5 6 7 4 24 3
57 1 7 4 7 3 39 3
58 1 6 7 7 6 70 3
59 1 7 2 0 0 48 3
60 1 7 7 0 5 42 3
61 1 7 3 7 1 63 3
62 1 7 0 3 0 23 3
63 1 7 7 6 3 58 3
64 1 7 3 0 0 10 3
65 1 0 0 0 0 0 1
66 1 3 0 0 0 0 3
67 1 7 7 7 5 73 3
68 1 7 7 7 6 39 3
69 1 7 7 7 7 54 3
70 1 7 2 6 5 52 3
71 1 6 4 6 0 39 3
72 1 7 7 3 0 61 3
73 1 7 3 0 0 34 3
74 1 7 7 6 6 30 3
75 1 7 7 7 3 100 3
76 1 7 6 5 2 55 3
77 1 7 5 4 0 58 3
78 1 7 5 5 0 49 3
79 1 7 5 2 0 18 3
80 2 1 0 0 0 0 1
81 2 0 0 0 0 13 1
82 2 1 0 1 0 0 1
83 2 5 3 4 1 32 2
84 2 3 0 0 0 0 1
85 2 7 4 1 0 36 2
86 2 5 5 1 0 20 2
87 2 5 3 4 2 23 2
88 2 7 6 3 1 39 2
89 2 1 0 1 1 14 1
90 2 7 0 4 4 54 2
91 2 4 0 0 0 36 2
92 2 2 0 0 0 0 1
93 2 7 6 0 6 29 2
94 2 7 1 0 1 11 2
95 2 4 0 0 0 5 2
96 2 7 7 5 2 64 2
97 2 7 7 1 2 52 2
98 2 7 7 1 0 19 2
99 2 5 2 2 1 28 2
100 2 7 4 0 0 22 2
101 2 7 7 6 0 68 2
102 2 7 6 0 0 39 2
103 2 7 7 7 0 60 2
104 2 7 7 7 3 78 2
105 2 6 0 0 0 11 2
106 2 7 6 0 0 59 2
107 2 7 4 4 0 28 2
108 2 7 7 7 1 64 2
109 2 7 0 0 0 8 2
110 2 5 0 1 3 64 2
111 2 7 5 7 7 72 2
112 2 4 2 0 2 50 2
113 2 7 6 7 0 44 2
114 2 7 1 0 0 11 2
115 2 7 3 0 0 16 2
116 2 7 0 0 0 30 2
117 2 5 4 5 0 14 2
118 2 2 7 0 0 10 1

119||2||2||0||0||1||20||1

120 2 3 0 0 0 7 1
121 2 7 2 2 2 10 2
122 2 7 6 5 2 58 2
123 2 7 1 0 0 19 2
124 2 2 6 0 1 41 1
125 2 7 3 0 0 17 2
126 2 5 2 2 0 5 2
127 2 7 5 0 2 49 2
128 2 7 2 0 0 36 2
129 2 4 0 4 4 73 2
130 2 4 1 0 0 19 2
131 2 4 7 3 0 40 2
132 2 7 4 6 1 43 2
133 2 5 0 4 0 22 2
134 2 7 3 1 0 32 2
135 2 7 7 3 0 70 2
136 2 7 5 0 3 35 2
137 2 7 7 5 0 35 2
138 2 7 6 6 0 35 2
139 2 7 0 0 0 8 2
140 2 5 0 0 0 5 2
141 2 7 1 0 0 33 2
142 2 7 7 4 0 46 2
143 2 7 4 0 0 15 2
144 2 5 7 0 0 11 2
145 2 6 0 0 0 9 2
146 2 6 0 0 0 12 2
147 2 7 0 0 0 2 2
148 2 7 7 3 0 43 2
149 2 7 7 2 2 73 2
150 2 7 6 4 0 38 2
151 2 7 4 0 0 11 2
152 2 7 7 7 3 60 2
153 2 7 1 0 0 27 2
154 2 7 0 0 0 25 2
155 2 6 6 2 0 2 2
156 2 7 0 0 0 12 2
157 2 1 0 0 0 0 1
158 2 2 0 0 0 18 1

References




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