The power of the classical twin study View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

1978-02

AUTHORS

N G Martin, L J Eaves, M J Kearsey, P Davies

ABSTRACT

A method based on the non-central chi-square distribution is developed for the calculation of sample sizes required to reject, with given probability, models of variation when they are “ wrong ”. The method is illustrated with reference to simple alternative models of variation in MZ and DZ twins reared together. Simulation of twin experiments finds the empirical power in good agreement with that predicted by the method. Tables are produced showing the sample sizes required for 95 per cent rejection at the 5 per cent level of inappropriate models of variation. For equivalent cases it is always found easier to reject an inappropriate simple genetical model of variation than an inappropriate simple environmental model. For several frequently encountered cases, more than 600 pairs of twins would be required to reject inappropriate alternative models. The optimum proportion of MZ and DZ twins in a sample will vary with the “true” model of variation but is most likely to be between two-thirds and one-half of DZ twin pairs. More... »

PAGES

hdy197810

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/hdy.1978.10

DOI

http://dx.doi.org/10.1038/hdy.1978.10

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1011399033

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/272366


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genetic Variation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Biological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Pregnancy", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Probability", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Twins", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "familyName": "Martin", 
        "givenName": "N G", 
        "type": "Person"
      }, 
      {
        "familyName": "Eaves", 
        "givenName": "L J", 
        "type": "Person"
      }, 
      {
        "familyName": "Kearsey", 
        "givenName": "M J", 
        "type": "Person"
      }, 
      {
        "familyName": "Davies", 
        "givenName": "P", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/hdy.1976.25", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000754186", 
          "https://doi.org/10.1038/hdy.1976.25"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1976.25", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000754186", 
          "https://doi.org/10.1038/hdy.1976.25"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1973.22", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001035210", 
          "https://doi.org/10.1038/hdy.1973.22"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1973.22", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001035210", 
          "https://doi.org/10.1038/hdy.1973.22"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1977.95", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001649853", 
          "https://doi.org/10.1038/hdy.1977.95"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1977.95", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001649853", 
          "https://doi.org/10.1038/hdy.1977.95"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1003585104", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4899-3404-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003585104", 
          "https://doi.org/10.1007/978-1-4899-3404-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4899-3404-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003585104", 
          "https://doi.org/10.1007/978-1-4899-3404-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2044-8317.1969.tb00426.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006620343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2044-8317.1970.tb00443.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006725445"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2044-8317.1977.tb00722.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009744821"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1975.14", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011600621", 
          "https://doi.org/10.1038/hdy.1975.14"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1975.14", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011600621", 
          "https://doi.org/10.1038/hdy.1975.14"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1469-1809.1975.tb00125.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013576630"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1970.61", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015241384", 
          "https://doi.org/10.1038/hdy.1970.61"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1970.61", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015241384", 
          "https://doi.org/10.1038/hdy.1970.61"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1037/h0029135", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016076574"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1037/h0032182", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027269653"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01070218", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030193160", 
          "https://doi.org/10.1007/bf01070218"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01070218", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030193160", 
          "https://doi.org/10.1007/bf01070218"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/263314a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030892738", 
          "https://doi.org/10.1038/263314a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1037/h0076862", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036926011"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01067145", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037916048", 
          "https://doi.org/10.1007/bf01067145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/240084a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047538492", 
          "https://doi.org/10.1038/240084a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1971.27", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052450506", 
          "https://doi.org/10.1038/hdy.1971.27"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/hdy.1971.27", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052450506", 
          "https://doi.org/10.1038/hdy.1971.27"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0021932000000493", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053747952"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.174.4016.1285", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062504038"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aoms/1177706453", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064401036"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2406136", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069915396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077356601", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01065758", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1080629861", 
          "https://doi.org/10.1007/bf01065758"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1558-5646.1959.tb03043.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085732985"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2344924", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103089213"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2344924", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103089213"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1978-02", 
    "datePublishedReg": "1978-02-01", 
    "description": "A method based on the non-central chi-square distribution is developed for the calculation of sample sizes required to reject, with given probability, models of variation when they are \u201c wrong \u201d. The method is illustrated with reference to simple alternative models of variation in MZ and DZ twins reared together. Simulation of twin experiments finds the empirical power in good agreement with that predicted by the method. Tables are produced showing the sample sizes required for 95 per cent rejection at the 5 per cent level of inappropriate models of variation. For equivalent cases it is always found easier to reject an inappropriate simple genetical model of variation than an inappropriate simple environmental model. For several frequently encountered cases, more than 600 pairs of twins would be required to reject inappropriate alternative models. The optimum proportion of MZ and DZ twins in a sample will vary with the \u201ctrue\u201d model of variation but is most likely to be between two-thirds and one-half of DZ twin pairs.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/hdy.1978.10", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1017442", 
        "issn": [
          "0018-067X", 
          "1365-2540"
        ], 
        "name": "Heredity", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "40"
      }
    ], 
    "name": "The power of the classical twin study", 
    "pagination": "hdy197810", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "364f128ebf8e96dde1299636d36edfab8f3731101185d9b9ed51bdbb765ac326"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "272366"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "0373007"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/hdy.1978.10"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1011399033"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/hdy.1978.10", 
      "https://app.dimensions.ai/details/publication/pub.1011399033"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:11", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000361_0000000361/records_53984_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://www.nature.com/articles/hdy197810"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/hdy.1978.10'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/hdy.1978.10'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/hdy.1978.10'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/hdy.1978.10'


 

This table displays all metadata directly associated to this object as RDF triples.

202 TRIPLES      21 PREDICATES      64 URIs      29 LITERALS      17 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/hdy.1978.10 schema:about N4e473fb995d94e2ca3e49df2dd94d780
2 N6d98a6d1048d475484d6b444331481e5
3 N72a53f72f8374f69b16733bdcfd2478c
4 N809bcab1febe495bb307213e8b2ef12b
5 Na085888dacf745c5908f0b1c0f1000ac
6 Ndce25e7e8c634d30b2323dc98b6a0904
7 Ne67a761f2c1b42949e8019d33d3f3def
8 Nf11d1e6041db49e2b4353cd22fc0ff00
9 anzsrc-for:01
10 anzsrc-for:0104
11 schema:author N0c877ab994184d06a3d682d950ed16a2
12 schema:citation sg:pub.10.1007/978-1-4899-3404-8
13 sg:pub.10.1007/bf01065758
14 sg:pub.10.1007/bf01067145
15 sg:pub.10.1007/bf01070218
16 sg:pub.10.1038/240084a0
17 sg:pub.10.1038/263314a0
18 sg:pub.10.1038/hdy.1970.61
19 sg:pub.10.1038/hdy.1971.27
20 sg:pub.10.1038/hdy.1973.22
21 sg:pub.10.1038/hdy.1975.14
22 sg:pub.10.1038/hdy.1976.25
23 sg:pub.10.1038/hdy.1977.95
24 https://app.dimensions.ai/details/publication/pub.1003585104
25 https://app.dimensions.ai/details/publication/pub.1077356601
26 https://doi.org/10.1017/s0021932000000493
27 https://doi.org/10.1037/h0029135
28 https://doi.org/10.1037/h0032182
29 https://doi.org/10.1037/h0076862
30 https://doi.org/10.1111/j.1469-1809.1975.tb00125.x
31 https://doi.org/10.1111/j.1558-5646.1959.tb03043.x
32 https://doi.org/10.1111/j.2044-8317.1969.tb00426.x
33 https://doi.org/10.1111/j.2044-8317.1970.tb00443.x
34 https://doi.org/10.1111/j.2044-8317.1977.tb00722.x
35 https://doi.org/10.1126/science.174.4016.1285
36 https://doi.org/10.1214/aoms/1177706453
37 https://doi.org/10.2307/2344924
38 https://doi.org/10.2307/2406136
39 schema:datePublished 1978-02
40 schema:datePublishedReg 1978-02-01
41 schema:description A method based on the non-central chi-square distribution is developed for the calculation of sample sizes required to reject, with given probability, models of variation when they are “ wrong ”. The method is illustrated with reference to simple alternative models of variation in MZ and DZ twins reared together. Simulation of twin experiments finds the empirical power in good agreement with that predicted by the method. Tables are produced showing the sample sizes required for 95 per cent rejection at the 5 per cent level of inappropriate models of variation. For equivalent cases it is always found easier to reject an inappropriate simple genetical model of variation than an inappropriate simple environmental model. For several frequently encountered cases, more than 600 pairs of twins would be required to reject inappropriate alternative models. The optimum proportion of MZ and DZ twins in a sample will vary with the “true” model of variation but is most likely to be between two-thirds and one-half of DZ twin pairs.
42 schema:genre research_article
43 schema:inLanguage en
44 schema:isAccessibleForFree true
45 schema:isPartOf N5dbe6f4de7484014a6f00bf1f5d00730
46 Nd06fc5fa057e4a67ba731d2db3aa6fdb
47 sg:journal.1017442
48 schema:name The power of the classical twin study
49 schema:pagination hdy197810
50 schema:productId N17827e1fc0c044f8be544c6bdf4ddef0
51 N77bc34a18a074b02baf08f9c60d8a4da
52 Nc4d31c30befe4d018431f5f5fcd6dffe
53 Nc8f9799971d1434aa84fa9fbc88809be
54 Nf61d6f3860b44118bc40d5d3445d0cf1
55 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011399033
56 https://doi.org/10.1038/hdy.1978.10
57 schema:sdDatePublished 2019-04-11T12:11
58 schema:sdLicense https://scigraph.springernature.com/explorer/license/
59 schema:sdPublisher Nea2e06d7fed54e4d81f648c8cc7338b8
60 schema:url http://www.nature.com/articles/hdy197810
61 sgo:license sg:explorer/license/
62 sgo:sdDataset articles
63 rdf:type schema:ScholarlyArticle
64 N0c877ab994184d06a3d682d950ed16a2 rdf:first N354310f7c3e24b8da68fbdd9c71643a2
65 rdf:rest Nc2589f082d1f4365b1ea934ab4c5ab45
66 N17827e1fc0c044f8be544c6bdf4ddef0 schema:name dimensions_id
67 schema:value pub.1011399033
68 rdf:type schema:PropertyValue
69 N354310f7c3e24b8da68fbdd9c71643a2 schema:familyName Martin
70 schema:givenName N G
71 rdf:type schema:Person
72 N4e473fb995d94e2ca3e49df2dd94d780 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
73 schema:name Pregnancy
74 rdf:type schema:DefinedTerm
75 N5dbe6f4de7484014a6f00bf1f5d00730 schema:volumeNumber 40
76 rdf:type schema:PublicationVolume
77 N6d98a6d1048d475484d6b444331481e5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
78 schema:name Female
79 rdf:type schema:DefinedTerm
80 N72a53f72f8374f69b16733bdcfd2478c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
81 schema:name Mathematics
82 rdf:type schema:DefinedTerm
83 N77bc34a18a074b02baf08f9c60d8a4da schema:name pubmed_id
84 schema:value 272366
85 rdf:type schema:PropertyValue
86 N809bcab1febe495bb307213e8b2ef12b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
87 schema:name Twins
88 rdf:type schema:DefinedTerm
89 N856af411931443d194dd054db4bb8b09 schema:familyName Davies
90 schema:givenName P
91 rdf:type schema:Person
92 Na085888dacf745c5908f0b1c0f1000ac schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
93 schema:name Models, Biological
94 rdf:type schema:DefinedTerm
95 Naf13a61b8f5f442a8d8329841c5dafde rdf:first N856af411931443d194dd054db4bb8b09
96 rdf:rest rdf:nil
97 Nc2589f082d1f4365b1ea934ab4c5ab45 rdf:first Nf0b587b9b89343a3b3f795f1af312e34
98 rdf:rest Nd48cd64f271c47549c19eaca0977462c
99 Nc4d31c30befe4d018431f5f5fcd6dffe schema:name nlm_unique_id
100 schema:value 0373007
101 rdf:type schema:PropertyValue
102 Nc8f9799971d1434aa84fa9fbc88809be schema:name readcube_id
103 schema:value 364f128ebf8e96dde1299636d36edfab8f3731101185d9b9ed51bdbb765ac326
104 rdf:type schema:PropertyValue
105 Nd06fc5fa057e4a67ba731d2db3aa6fdb schema:issueNumber 1
106 rdf:type schema:PublicationIssue
107 Nd48cd64f271c47549c19eaca0977462c rdf:first Nea962a2851944efca52f00caac5c7606
108 rdf:rest Naf13a61b8f5f442a8d8329841c5dafde
109 Ndce25e7e8c634d30b2323dc98b6a0904 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
110 schema:name Humans
111 rdf:type schema:DefinedTerm
112 Ne67a761f2c1b42949e8019d33d3f3def schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
113 schema:name Probability
114 rdf:type schema:DefinedTerm
115 Nea2e06d7fed54e4d81f648c8cc7338b8 schema:name Springer Nature - SN SciGraph project
116 rdf:type schema:Organization
117 Nea962a2851944efca52f00caac5c7606 schema:familyName Kearsey
118 schema:givenName M J
119 rdf:type schema:Person
120 Nf0b587b9b89343a3b3f795f1af312e34 schema:familyName Eaves
121 schema:givenName L J
122 rdf:type schema:Person
123 Nf11d1e6041db49e2b4353cd22fc0ff00 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
124 schema:name Genetic Variation
125 rdf:type schema:DefinedTerm
126 Nf61d6f3860b44118bc40d5d3445d0cf1 schema:name doi
127 schema:value 10.1038/hdy.1978.10
128 rdf:type schema:PropertyValue
129 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
130 schema:name Mathematical Sciences
131 rdf:type schema:DefinedTerm
132 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
133 schema:name Statistics
134 rdf:type schema:DefinedTerm
135 sg:journal.1017442 schema:issn 0018-067X
136 1365-2540
137 schema:name Heredity
138 rdf:type schema:Periodical
139 sg:pub.10.1007/978-1-4899-3404-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003585104
140 https://doi.org/10.1007/978-1-4899-3404-8
141 rdf:type schema:CreativeWork
142 sg:pub.10.1007/bf01065758 schema:sameAs https://app.dimensions.ai/details/publication/pub.1080629861
143 https://doi.org/10.1007/bf01065758
144 rdf:type schema:CreativeWork
145 sg:pub.10.1007/bf01067145 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037916048
146 https://doi.org/10.1007/bf01067145
147 rdf:type schema:CreativeWork
148 sg:pub.10.1007/bf01070218 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030193160
149 https://doi.org/10.1007/bf01070218
150 rdf:type schema:CreativeWork
151 sg:pub.10.1038/240084a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047538492
152 https://doi.org/10.1038/240084a0
153 rdf:type schema:CreativeWork
154 sg:pub.10.1038/263314a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030892738
155 https://doi.org/10.1038/263314a0
156 rdf:type schema:CreativeWork
157 sg:pub.10.1038/hdy.1970.61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015241384
158 https://doi.org/10.1038/hdy.1970.61
159 rdf:type schema:CreativeWork
160 sg:pub.10.1038/hdy.1971.27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052450506
161 https://doi.org/10.1038/hdy.1971.27
162 rdf:type schema:CreativeWork
163 sg:pub.10.1038/hdy.1973.22 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001035210
164 https://doi.org/10.1038/hdy.1973.22
165 rdf:type schema:CreativeWork
166 sg:pub.10.1038/hdy.1975.14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011600621
167 https://doi.org/10.1038/hdy.1975.14
168 rdf:type schema:CreativeWork
169 sg:pub.10.1038/hdy.1976.25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000754186
170 https://doi.org/10.1038/hdy.1976.25
171 rdf:type schema:CreativeWork
172 sg:pub.10.1038/hdy.1977.95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001649853
173 https://doi.org/10.1038/hdy.1977.95
174 rdf:type schema:CreativeWork
175 https://app.dimensions.ai/details/publication/pub.1003585104 schema:CreativeWork
176 https://app.dimensions.ai/details/publication/pub.1077356601 schema:CreativeWork
177 https://doi.org/10.1017/s0021932000000493 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053747952
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1037/h0029135 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016076574
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1037/h0032182 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027269653
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1037/h0076862 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036926011
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1111/j.1469-1809.1975.tb00125.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1013576630
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1111/j.1558-5646.1959.tb03043.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1085732985
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1111/j.2044-8317.1969.tb00426.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1006620343
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1111/j.2044-8317.1970.tb00443.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1006725445
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1111/j.2044-8317.1977.tb00722.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1009744821
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1126/science.174.4016.1285 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062504038
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1214/aoms/1177706453 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064401036
198 rdf:type schema:CreativeWork
199 https://doi.org/10.2307/2344924 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103089213
200 rdf:type schema:CreativeWork
201 https://doi.org/10.2307/2406136 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069915396
202 rdf:type schema:CreativeWork
 




Preview window. Press ESC to close (or click here)


...